CA2159973C - Message filtering techniques - Google Patents
Message filtering techniquesInfo
- Publication number
- CA2159973C CA2159973C CA002159973A CA2159973A CA2159973C CA 2159973 C CA2159973 C CA 2159973C CA 002159973 A CA002159973 A CA 002159973A CA 2159973 A CA2159973 A CA 2159973A CA 2159973 C CA2159973 C CA 2159973C
- Authority
- CA
- Canada
- Prior art keywords
- message
- expertise
- addressee
- computer system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/107—Computer-aided management of electronic mailing [e-mailing]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/21—Monitoring or handling of messages
- H04L51/212—Monitoring or handling of messages using filtering or selective blocking
Abstract
Techniques for reducing the amount of junk e-mail received by a user of an e-mail system. A recipient description containing non-address information is added to an e-mail message. The user has an e-mail filter which has access to information which provides a model of the user. The e-mail filter uses the non-address information and the model information to determine whether the e-mail message should be providedto the user. The e-mail filter further has access to information which provides models of the user's correspondents. If the filter does not provide the message to the user, it uses the non-address information and the model information of the user's correspondents to determine who the message might be forwarded to. A sender of e-mail can also use the model information of the sender's correspondents together with the non-address information to determine who the message should be sent to.The techniques are used in a system for locating exp ertise.
Description
~I~~9'~3 Message Filtering Techniques 1 Background of the Invention 1.1 Field of the Invention The invention concerns electronic messaging in general and electronic mail in particular.
1.2 Description of the Prior Art A major annoyance in the conventional mail system is junk mail. As elec-tronic mail has grown in availability and popularity, junk electronic mail has become a problem as well. Indeed, the ease with which an e-mail message ' may be sent to many recipients may eventually make junk e-mail an even worse problem that junk conventional mail.
The prior art has attempted to deal with the junk e-mail problem by means of rrcaal filters in an e-mail recipient's local e-mail system. Such a filter sorts incoming e-mail for the recipient into categories determined by the recipient. The filter simply scans each e-mail message as it reaches the 21599'3 recipient and determines what category it should be placed in. One category is of course "discard" . Messages which the filter places in that category are automatically discarded. Prior-art filters have had varying degrees of intel-ligence; some have simply worked with lists of source addresses and have sorted according to the source of the message; others have used keywords provided by the recipient to sort; with others, finally, the filter observes how the recipient sorts his email for awhile and is then able to sort in a simi-lar fashion. For details about mail filters, see Peter W. Foltz and Susan T.
Dumais, "Personalized information delivery: an analysis of information fil-tering methods", Communications of the ACM, vol. 35, no. 12, Dec., 1992, pp. 51-60; D.K. Gifford, R.W. Baldwin, S.T. Berlin, J.M. Lucassen, "An architecture for large scale information systems", in Proceedings Tenth Sym-posium on Operating Systems Principles, (Orcas Island, Wash., Dec 1985), pp. 161-170; E. Lutz, H.V. Kleist-Retzow, and K. Hoerning, "MAFIA - An active mail-filter agent for an intelligent document processing support", in M~Iti-User Interfaces and Applications, S. Gibbs andn A.A. Verrijn-Stuart, Eds, North Holland, 1990, pp. 16-32; T.W. Malone, K.R. Grant, F.A. Tur-bak, S.A. Browst, M.D. Cohen, "Intelligent information sharing systems", Common. ACM 30, 5 (May 1987) 390-402; S. Pollack, "A rule-based mes-sage filtering system", ACM Trans. 0,,~: Inf. Syst. 6, 3 (July 1988), 232-254.
P. Maes, "Agents that Reduce Work and Information Overload", Common.
ACM 37 (7) (July 1994), pp. 31-40. A problem with all such filters is that sorting for another person is difF~cult even for a human being, and if a filter is going to be useful, it cannot do much worse than a human would.
One of the reasons for the junk mail is that present-day e-mail systems require that recipients be addressed by e-mail addresses. In order to ensure that an e-mail message will reach everyone who might possibly be interested in it, the sender typically uses a list of addresses which includes those who might be interested but includes many others as well. For everyone but those actually interested, the e-mail is of course junk mail.
What is needed to reduce the amount of junk mail is a technique which permits a sender to use something in addition to the e-mail address to specify the kinds of people who are to actually receive the e-mail and permits a filter to use the information provided by the sender to filter the mail so that only those kinds of people actually receive it. It is an object of the invention disclosed herein to provide such a technique and thereby to reduce the amount of junk e-mail received by a user of the e-mail system.
2 S ummary of t he Invent ion The invention reduces the amount of junk e-mail received by a user of the e-mail system by adding a recipient specifies to an e-mail message. The recip-ient specifies non-address information to further specify the recipients in the group to whom the message is sent who should actually receive the message.
The mail filter for a given recipient has access to information about that re-cipient and uses that information together with the non-address information in the e-mail message to determine whether the message should be provided to the given recipient. If the non-address information and the information about the recipient indicate that the given recipient should not receive the message, the filter does not provide it.
1.2 Description of the Prior Art A major annoyance in the conventional mail system is junk mail. As elec-tronic mail has grown in availability and popularity, junk electronic mail has become a problem as well. Indeed, the ease with which an e-mail message ' may be sent to many recipients may eventually make junk e-mail an even worse problem that junk conventional mail.
The prior art has attempted to deal with the junk e-mail problem by means of rrcaal filters in an e-mail recipient's local e-mail system. Such a filter sorts incoming e-mail for the recipient into categories determined by the recipient. The filter simply scans each e-mail message as it reaches the 21599'3 recipient and determines what category it should be placed in. One category is of course "discard" . Messages which the filter places in that category are automatically discarded. Prior-art filters have had varying degrees of intel-ligence; some have simply worked with lists of source addresses and have sorted according to the source of the message; others have used keywords provided by the recipient to sort; with others, finally, the filter observes how the recipient sorts his email for awhile and is then able to sort in a simi-lar fashion. For details about mail filters, see Peter W. Foltz and Susan T.
Dumais, "Personalized information delivery: an analysis of information fil-tering methods", Communications of the ACM, vol. 35, no. 12, Dec., 1992, pp. 51-60; D.K. Gifford, R.W. Baldwin, S.T. Berlin, J.M. Lucassen, "An architecture for large scale information systems", in Proceedings Tenth Sym-posium on Operating Systems Principles, (Orcas Island, Wash., Dec 1985), pp. 161-170; E. Lutz, H.V. Kleist-Retzow, and K. Hoerning, "MAFIA - An active mail-filter agent for an intelligent document processing support", in M~Iti-User Interfaces and Applications, S. Gibbs andn A.A. Verrijn-Stuart, Eds, North Holland, 1990, pp. 16-32; T.W. Malone, K.R. Grant, F.A. Tur-bak, S.A. Browst, M.D. Cohen, "Intelligent information sharing systems", Common. ACM 30, 5 (May 1987) 390-402; S. Pollack, "A rule-based mes-sage filtering system", ACM Trans. 0,,~: Inf. Syst. 6, 3 (July 1988), 232-254.
P. Maes, "Agents that Reduce Work and Information Overload", Common.
ACM 37 (7) (July 1994), pp. 31-40. A problem with all such filters is that sorting for another person is difF~cult even for a human being, and if a filter is going to be useful, it cannot do much worse than a human would.
One of the reasons for the junk mail is that present-day e-mail systems require that recipients be addressed by e-mail addresses. In order to ensure that an e-mail message will reach everyone who might possibly be interested in it, the sender typically uses a list of addresses which includes those who might be interested but includes many others as well. For everyone but those actually interested, the e-mail is of course junk mail.
What is needed to reduce the amount of junk mail is a technique which permits a sender to use something in addition to the e-mail address to specify the kinds of people who are to actually receive the e-mail and permits a filter to use the information provided by the sender to filter the mail so that only those kinds of people actually receive it. It is an object of the invention disclosed herein to provide such a technique and thereby to reduce the amount of junk e-mail received by a user of the e-mail system.
2 S ummary of t he Invent ion The invention reduces the amount of junk e-mail received by a user of the e-mail system by adding a recipient specifies to an e-mail message. The recip-ient specifies non-address information to further specify the recipients in the group to whom the message is sent who should actually receive the message.
The mail filter for a given recipient has access to information about that re-cipient and uses that information together with the non-address information in the e-mail message to determine whether the message should be provided to the given recipient. If the non-address information and the information about the recipient indicate that the given recipient should not receive the message, the filter does not provide it.
In another aspect of the invention, the sender's mail filter does the filtering. The sender provides a recipient specifier which uses non-address information to specify potential recipients to the mail filter. In this aspect, however, the sender's mail filter has access to information about the possible recipients and uses this information together with the non-address information to determine the potential recipients to whom the message should be sent.
The first and second aspects of the invention are combined in a further aspect of the invention, namely a system for locating expertise in the e-mail system. In this system, the sender specifies an area of expertise by means of a list of keywords which are relevant to the area. The list of keywords is included in a recipient specifier in the message. The mail filter for a potential recipient has access to the document files of the potential recipient and to a list of the e-mail messages sent and received by the potential recipient. The mail filter uses the document files to determine the recipient's area of expertise. If the keywords in the recipient specifier match one of the areas of expertise, the mail filter provides the e-mail message to the potential recipient; if not, the mail filter uses the list of e-mail messages to determine correspondents of the potential recipient who may have the area of expertise specified in the recipient specifier and forwards the message to those correspondents.
The mail filter of each potential recipient which actually provides the message to the recipient further sends a referral message to the sender of the message, who thus knows exactly who received the message.
In accordance with one aspect of the present invention there is provided apparatus for automatically limiting the recipients of a message sent via a mail system implemented in a computer system, the apparatus comprising: recipient specifying means in the message which uses non-address information to specify the recipients of the message; message filtering means in the computer system having access to recipient information contained therein about at least one potential recipient and including means responsive to the non-address information and to the recipient A
information for providing the message to the at least one potential recipient if the non-address information and the recipient information together indicate that the at least one potential recipient is to receive the message; and means, in the message filtering means, for sending a referral message to a source of the message when the message filtering means provides the message to the at least one potential recipient.
Other objects and advantages of the apparatus and methods disclosed 4a A
herein will be apparent to those of ordinary skill in the art upon perusal of the following Drawing and Detailed Description, wherein:
3 Brief Description of the Drawing FIG. 1 is a high-level block diagram of apparatus embodying the invention;
FIG. 2 is a diagram of user model 113 in a preferred embodiment;
FIG. 3 is a diagram of correspondent models 111 in a preferred embodment;
and FIG. 4 is a diagram of data structures used by mail filter 109 in a pre-ferred embodiment.
Reference numbers in the Drawing have two parts: the two least-significant digits are the number of an item in a figure; the remaining digits are the number of the figure in which the item first appears. Thus, an item with the reference number 201 first appears in FIG. 2.
4 Detailed Description of a Preferred Em-bodiment The following Detailed Description begins with an overview of the invention and then describes in detail how the invention is implemented in apparatus to locate expertise in an e-mail system.
g Overview of the invention: FIG. 1 FIG. 1 shows a high-level overview of apparatus 101 which embodies the invention. Apparatus 101 is employed in a network 103 which connects a number of users 105(a..n). Network 103 may be a network such as Inter-net or a commercial e-mail network, or it may be an e-mail system which communicates between users of a single computer system. Each user 105 is connected to network 103 by means of a link 107 over which user 105 can send and receive e-mail messages. A mail item of the type used in the inven-tion is shown at 119; mail item 119 is a standard e-mail message except for two additional components:
1. recipient specifies 121 which uses non-address information to further describe the recipients who should receive the e-mail; and 2. referral list 127, which is a list of potential recipients who passed the e-mail on and of recipients to whom the e-mail was provided.
Recipient specifies 121 has two parts, recipient type field 123, which gener-ally indicates how recipient specifies 121 is to be interpreted, and recipient description 125, which contains the non-address information which is actu-ally used to determine whether mail item 119 is to be provided to a given recipient.
A user 105 who wishes to reduce the amount of junk e-mail he receives has a mail filter 109 as part of his e-mail system. When an e-mail item 119 is sent to user 105's address, mail filter 109 interprets recipient specifies to determine whether mail item 119 is to be provided to user 105(n). In interpreting recipient specifier 109, mail filter 109 employs user model 113, which is data that provides a model of user 105(n). If recipient description 125 specifies a recipient which is of the same kind as that specified by user model 113, mail filter 109 adds mail item 119 to filtered mail 115 and informs user 105(n) via interactive user mail interface 117 that mail has arrived. If user 105(n) desires, mail filter 109 can further use the information in referral list 127 to indicate the chain of referrals which resulted in the message being directed to user 105(n). In some embodiments, mail filter 109 may also use the information in referral list 127 to send a receipt 129 which identifies the e-mail message, the chain of referrals, and user 105(n) to the original sender of mail item 119.
If user model 113 does not specify a recipient which is of the same kind specified by recipient description 125, mail filter 109 looks to correspondent models 111 to determine where to send mail item 119. There is a correspon-dent model 111(m) for each of user 105(n)'s frequent correspondents, and like user model 113, each correspondent model 111(m) contains data which mail filter 109 can use together with recipient description 125 to determine which of user 105(n)'s correspondents should receive mail item 119. Mail fil-ter 109 then adds the names and e-mail addresses of those correspondents to referral list 127 in mail item 119 and forwards mail item 119 to those corre-spondents. If they in turn have mail filters 109, they will also filter mail item 119 as just described. In a preferred embodiment, user 105(n) may specify how much control he desires over forwarding. Forwarding may be completely automatic, or mail filter 109 may present user 105(n) with the information from recipient description 125 and a list of the correspondents it has found ~~.5g9'~3 for forwarding and let user 105(n) select which of the correspondents is to receive the forwarded letter.
If user 105(n) wishes to send an e-mail message with a recipient specifier 121, user 105(n) makes that request of mail filter 109. Mail filter 109 uses interface 117 to obtain information from user 105(n) which it uses to make recipient specifier 121. Mail filter 109 then uses recipient specifier 121 with correspondent models 111 in the manner described above to make a list of the correspondents who should receive the message. Depending on the implementation, mail filter 109 may simply send the e-mail message to those correspondents or permit user 105(n) to select correspondents from the list.
The selected correspondents will of course be placed on referral list 127.
In FIG. 1, mail filter 109 and correspondent models 111 and user model 113 are all implemented in the local computer system used by user 105(n).
Such an implementation is advantageous in that the information in corre-spondent models 111 and user model 113 remains under the control of user 105(n). In other embodiments, however, mail filter 109 may be located at any point in network 103. Indeed, some embodiments may contain only cor-respondent models 111. For example, a data base of customer information might be used as a correspondent model 111, and mail filter 109 might use recipient description 125 together with the data base of customer information to determine which customers should receive e-mail about a new product or service.
The first and second aspects of the invention are combined in a further aspect of the invention, namely a system for locating expertise in the e-mail system. In this system, the sender specifies an area of expertise by means of a list of keywords which are relevant to the area. The list of keywords is included in a recipient specifier in the message. The mail filter for a potential recipient has access to the document files of the potential recipient and to a list of the e-mail messages sent and received by the potential recipient. The mail filter uses the document files to determine the recipient's area of expertise. If the keywords in the recipient specifier match one of the areas of expertise, the mail filter provides the e-mail message to the potential recipient; if not, the mail filter uses the list of e-mail messages to determine correspondents of the potential recipient who may have the area of expertise specified in the recipient specifier and forwards the message to those correspondents.
The mail filter of each potential recipient which actually provides the message to the recipient further sends a referral message to the sender of the message, who thus knows exactly who received the message.
In accordance with one aspect of the present invention there is provided apparatus for automatically limiting the recipients of a message sent via a mail system implemented in a computer system, the apparatus comprising: recipient specifying means in the message which uses non-address information to specify the recipients of the message; message filtering means in the computer system having access to recipient information contained therein about at least one potential recipient and including means responsive to the non-address information and to the recipient A
information for providing the message to the at least one potential recipient if the non-address information and the recipient information together indicate that the at least one potential recipient is to receive the message; and means, in the message filtering means, for sending a referral message to a source of the message when the message filtering means provides the message to the at least one potential recipient.
Other objects and advantages of the apparatus and methods disclosed 4a A
herein will be apparent to those of ordinary skill in the art upon perusal of the following Drawing and Detailed Description, wherein:
3 Brief Description of the Drawing FIG. 1 is a high-level block diagram of apparatus embodying the invention;
FIG. 2 is a diagram of user model 113 in a preferred embodiment;
FIG. 3 is a diagram of correspondent models 111 in a preferred embodment;
and FIG. 4 is a diagram of data structures used by mail filter 109 in a pre-ferred embodiment.
Reference numbers in the Drawing have two parts: the two least-significant digits are the number of an item in a figure; the remaining digits are the number of the figure in which the item first appears. Thus, an item with the reference number 201 first appears in FIG. 2.
4 Detailed Description of a Preferred Em-bodiment The following Detailed Description begins with an overview of the invention and then describes in detail how the invention is implemented in apparatus to locate expertise in an e-mail system.
g Overview of the invention: FIG. 1 FIG. 1 shows a high-level overview of apparatus 101 which embodies the invention. Apparatus 101 is employed in a network 103 which connects a number of users 105(a..n). Network 103 may be a network such as Inter-net or a commercial e-mail network, or it may be an e-mail system which communicates between users of a single computer system. Each user 105 is connected to network 103 by means of a link 107 over which user 105 can send and receive e-mail messages. A mail item of the type used in the inven-tion is shown at 119; mail item 119 is a standard e-mail message except for two additional components:
1. recipient specifies 121 which uses non-address information to further describe the recipients who should receive the e-mail; and 2. referral list 127, which is a list of potential recipients who passed the e-mail on and of recipients to whom the e-mail was provided.
Recipient specifies 121 has two parts, recipient type field 123, which gener-ally indicates how recipient specifies 121 is to be interpreted, and recipient description 125, which contains the non-address information which is actu-ally used to determine whether mail item 119 is to be provided to a given recipient.
A user 105 who wishes to reduce the amount of junk e-mail he receives has a mail filter 109 as part of his e-mail system. When an e-mail item 119 is sent to user 105's address, mail filter 109 interprets recipient specifies to determine whether mail item 119 is to be provided to user 105(n). In interpreting recipient specifier 109, mail filter 109 employs user model 113, which is data that provides a model of user 105(n). If recipient description 125 specifies a recipient which is of the same kind as that specified by user model 113, mail filter 109 adds mail item 119 to filtered mail 115 and informs user 105(n) via interactive user mail interface 117 that mail has arrived. If user 105(n) desires, mail filter 109 can further use the information in referral list 127 to indicate the chain of referrals which resulted in the message being directed to user 105(n). In some embodiments, mail filter 109 may also use the information in referral list 127 to send a receipt 129 which identifies the e-mail message, the chain of referrals, and user 105(n) to the original sender of mail item 119.
If user model 113 does not specify a recipient which is of the same kind specified by recipient description 125, mail filter 109 looks to correspondent models 111 to determine where to send mail item 119. There is a correspon-dent model 111(m) for each of user 105(n)'s frequent correspondents, and like user model 113, each correspondent model 111(m) contains data which mail filter 109 can use together with recipient description 125 to determine which of user 105(n)'s correspondents should receive mail item 119. Mail fil-ter 109 then adds the names and e-mail addresses of those correspondents to referral list 127 in mail item 119 and forwards mail item 119 to those corre-spondents. If they in turn have mail filters 109, they will also filter mail item 119 as just described. In a preferred embodiment, user 105(n) may specify how much control he desires over forwarding. Forwarding may be completely automatic, or mail filter 109 may present user 105(n) with the information from recipient description 125 and a list of the correspondents it has found ~~.5g9'~3 for forwarding and let user 105(n) select which of the correspondents is to receive the forwarded letter.
If user 105(n) wishes to send an e-mail message with a recipient specifier 121, user 105(n) makes that request of mail filter 109. Mail filter 109 uses interface 117 to obtain information from user 105(n) which it uses to make recipient specifier 121. Mail filter 109 then uses recipient specifier 121 with correspondent models 111 in the manner described above to make a list of the correspondents who should receive the message. Depending on the implementation, mail filter 109 may simply send the e-mail message to those correspondents or permit user 105(n) to select correspondents from the list.
The selected correspondents will of course be placed on referral list 127.
In FIG. 1, mail filter 109 and correspondent models 111 and user model 113 are all implemented in the local computer system used by user 105(n).
Such an implementation is advantageous in that the information in corre-spondent models 111 and user model 113 remains under the control of user 105(n). In other embodiments, however, mail filter 109 may be located at any point in network 103. Indeed, some embodiments may contain only cor-respondent models 111. For example, a data base of customer information might be used as a correspondent model 111, and mail filter 109 might use recipient description 125 together with the data base of customer information to determine which customers should receive e-mail about a new product or service.
215 9 9 '~ ~
A System for Locating Expertise The techniques described above are employed in a preferred embodiment to make a system for locating expertise. The following discussion first explains the utility of such a system and then presents two different embodiments.
Using a Computer to Find Information There are basically two ways of finding something out by using a computer:
"ask a program" and "ask a person" .
The first covers all ways of accessing information stored online, including the use of traditional database programs; file indexing and retrieval programs such as glimpse (by Udi Manber at University of Arizona) or Apple's Apple-Search; news filtering programs such as Hoover (SandPoint Corp.); and. even more simply, the use of tools such as ftp, awk, and text editors to retrieve and view files.
The second, "ask a person", covers ways that a computer can be used ~ a communication medium between people. Currently the prime examples are electronic mail, including both personal e-mail and mailing lists, and bulletin boards and newsgroups. The growing integration of computers and telephones allows us to also view telephony as a computer-based communica-tion medium. Simple examples of such integration are telephone address book programs that run on a personal or pocket computer and dial numbers for you; more sophisticated is the explosion in the use of computer-based FAX.
Today it is hard to even buy a modem that does not have FAX capability, and by far the heaviest use of FAX is for person-to-person communication.
A System for Locating Expertise The techniques described above are employed in a preferred embodiment to make a system for locating expertise. The following discussion first explains the utility of such a system and then presents two different embodiments.
Using a Computer to Find Information There are basically two ways of finding something out by using a computer:
"ask a program" and "ask a person" .
The first covers all ways of accessing information stored online, including the use of traditional database programs; file indexing and retrieval programs such as glimpse (by Udi Manber at University of Arizona) or Apple's Apple-Search; news filtering programs such as Hoover (SandPoint Corp.); and. even more simply, the use of tools such as ftp, awk, and text editors to retrieve and view files.
The second, "ask a person", covers ways that a computer can be used ~ a communication medium between people. Currently the prime examples are electronic mail, including both personal e-mail and mailing lists, and bulletin boards and newsgroups. The growing integration of computers and telephones allows us to also view telephony as a computer-based communica-tion medium. Simple examples of such integration are telephone address book programs that run on a personal or pocket computer and dial numbers for you; more sophisticated is the explosion in the use of computer-based FAX.
Today it is hard to even buy a modem that does not have FAX capability, and by far the heaviest use of FAX is for person-to-person communication.
21~997~
There are inherent problems with both general approaches to obtaining information. It has often been noted that as the world of online information sources expands, the "ask a program" approach suffers from the problem of knowing where to look. For example, the Mosaic system overcomes many of the technical problems in accessing a wide variety of information on the Internet, by automatically handling the low-level details of different commu-nication protocols. It is easy and entertaining to browse through an enormous hypermedia space. However, finding an answer to a specific question using Mosaic tends to be slow and frustrating, and often results in failure. One response to this problem has been the attempt to design systems that incor-porate knowledge about the location of information, such as the Information Manifold project (by T. Kirk, A. Levy, and D. Srivastava, of AT&T Bell Labs). However, a deeper problem remains, that no solution based solely on building a better search-engine can address. This is the fact that much valuable information is simply not online, but only exists in people's heads.
Furthermore, there are economic, social, and political reasons that much valuable information will never be made publicly accessible on the Internet or any other network. Indeed, part of the value of a piece of information resides in the degree to which it is not easily accessible.
In any large organization, determining who is an expert on a particular topic is a crucial problem. The need for expertise location ranges from in-formal situations, such as where I might need to find an expert on LaTex macros to help fix a typesetting problem in a paper I'm writing, to formal construction of project teams to meet business needs. The range of expertise specifications may range from the generic ( "who knows about logic program-ming?" ) to the highly specific ( "who knows how to modify the interrupt vector handling microcode in the reboot module of the XZY999 processor?" ).
Online directories of expertise rarely exist, and when they do, the infor mation they contain is certain to be out of date and incomplete. In fact, expertise needs are potentially so specific that it is simply impossible to de termine a comprehensive set of categories in advance. Expertise location is therefore generally an "ask a person" task, with all the problems associated with that approach outlined above.
Let us consider for a moment how expertise location actually works when it is successful. In a typical case I contact a small set of colleagues whom I think might be familiar with the topic. Because each person knows me personally, they are quite likely to respond. Usually none of them is exactly the person I want; however, they can refer me to someone they know who might be. After following a chain of referrals a few layers deep I finally find the person I want.
Note that in this successful scenario I needed to walk a fine line between contacting too few people (and thus not finding the true expert) and con-tacting too many (and eventually making a pest of myself). Even in the end I might wonder if I might not have found even a better expert if only I could have cast the net a bit wider. I may have had dif&culty bringing to mind those people I do know personally who have some expertise in the desired area. If only all of my colleagues employed endlessly patient assistants that I
could have contacted initially, who would have known something about their bosses' areas of expertise, and who could have answered my initial queries without disturbing everyone...
A
Now let us consider how mail filters could be used to augment the expert location process. Each person's mail filter would create a model of that person's areas of interest. This model would be created automatically by using information retrieval (IR) techniques (such as inverted indexes) on all the documents created and received by the user. The user model could be quite large and detailed, and would be private to the user, that is, not stored in a central database. The mail filter would also create a much more coarse-grained model of my contacts by applying similar techniques to all the electronic mail that I exchange with each person.
When I have an expertise location need, I present the problem to my mail filter as an unstructured text description. Again using IR techniques, my mail filter selects a medium-to-large set of my contacts to whom the query may be relevant. It then broadcasts the query, not to the people themselves, but to their mail filters. Upon receipt of the question, each mail filter checks if its owner's user model does indeed provide a good match. If there is a good match, the mail filter presents my request to its owner. If the owner's model does not match, but the model of one of the owner's contacts does, then the mail filter can ask the owner if it can provide a referral. Finally, if there is no match at all, the query is silently logged and deleted. A great deal of flexibility can be built into each mail filter, depending upon its owner's preferences. For example, I might allow automatic referrals to be given to requests that come from my closest colleagues.
This system provides several benefits over either sending personal e-mail to everyone in order to find an expert or using netnews to find the expert.
First, it is largely passive on the part of the recipients - they do not need to -~- 21 5 9 9 7 3 be reading netnews and wading through dozens of articles. Second, queries are broadcast in a focused manner to those who are at least somewhat likely to find them of interest. Third, users are shielded from seeing a large number of completely irrelevant messages; each mail filter 109 may process dozens of messages for every one the user sees. Finally, messages that a user does see do not come from "out of the blue", but rather are tagged with a chain of referrals from colleague to colleague.
One reason to believe that the system just described would be useful in practice is that it basically models the manner in which expertise location actually works now (D. Krackhardt and J. R. Hanson, "Informal Networks: The Company Behind the Chart", Harvard Business Review, July-August 1993), while allowing more people to be contacted without causing disruption and disturbance.
Implementation of an Expertise Locator A presently-preferred embodiment of the expertise locator has been implemented using network agents described in Coen, et al., Network Agents, European Patent EP
669733. In the implementation, mail filter 109 is a component of a user agent which handles e-mail messages for its user. Mail filters 109 are written in the programming language Visual Basic, and run on a standard personal computer. Interactive user mail interface 117 presents the expertise locator in mail filter 109 to the user as an anthropomorphic "talking head" that appears in a window on the computer screen. All the computers running mail filters 109 are networked (currently A
using the protocol TCP/IP), and can exchange electronic mail with each other and with any person. A mail filter 109 can also invoke other programs to perform various subtasks.
Each mail filter 109 has access to two sets of data base files. The first set, shown in FIG. 2, implements correspondent models 111; the second set, shown in FIG. 3, implements user model 113. Each of the data base files in the two sets is specific to and owned by the individual user of mail filter 109.
It is important to note that we do not assume that these files can be directly accessed by anyone other than the user and mail filter 109.
Correspondent models 111 contains the following five files:
~ Colleague list 201 which contains entries 203 for some of the user's colleagues. Each entry 203 contains an identification 205 for the col-league and each a list of keywords 207 describing the colleague's areas of expertise.
~ An Email file 209 which contains all of the email 211(O..n) that the user has sent and received for a substantial period of time: typically, the past year or several years.
~ An Email inverted index file 213 that has an entry 215 for each word that appears in any email message. Entry 215 contains a word 217 and a list of the numbers of the messages in email file 209 that contain that word. This kind of file can be generated using standard information retrieval algorithms, such as those described in (G. Salton, Automatic Text Processing, Addison-Wesley 1989).
~ A sender/recipient list file 221 that has an entry 223 for each message in email file 209. The entry contains the identifier of the sender of the corresponding message (if other than the user) or the identifier of the recipient of the corresponding message (if sent by the user).
FIG. 3 shows the data base files used to implement user model 113.
~ User expertise list 301 is a file containing a list of keywords that describe some of the user's own areas of expertise.
~ User files inverted index 305 is a file containing an inverted index of text files in the user's directory. That is, for every word that appears in any file the user has stored on the computer, this file contains a list of the names of the files containing that word.
In the preferred embodiment, colleague list 201 and user expertise list 301 are created by mail filter 109 in interaction with user 105(n); the inverted index files 213 and user files inverted index 305 are created automatically by mail filter 109. This kind of very large inverted index can be quickly created and searched by the program "glimpse" (U. Manber and S. Wu, "GLIMPSE: A
Tool to Search Through Entire File Systems," Usenix Winter 199 Technical Conference, San Francisco (January 1994), pp. 23-32). In making inverted list 305, GLIMPSE uses a UNIX operating system (UNIX is a trademark of XOPEN) utility which determines whether a file is a text file. In addition, the user can specify to GLIMPSE which directories of files or individual files are to be indexed.
A user begins the process of locating an expert in a topic by clicking on the window for mail filter 109 and typing a phrase that describes the general 21599?3 kind of request (such as, "I need to locate an expert"). Mail filter 109 then prompts the user for a phrase describing the area of expertise. Once this is done, mail filter 109 generates and presents for approval a list of suggested candidates for receiving the request.
The list of candidates is generated by combining names from two sources.
First, names are added that appear in colleague list 201, such that the words that appear in the phrase describing the expertise request appear in the list of keywords 207 associated with name 205.
Second, names are added that result from the following computation.
First, for each word that appears in the expertise request, mail filter 109 retrieves from email inverted index file 213 a list of messages 403(O..n) (FIG.
4) containing that word. Next, the intersection of the lists is computed, generating a list of messages 405 each of which appears in every one of the previous lists. Next, list of messages 405 is compared against sender/recipient list file 221, and the total number of messages that appear in list of messages 405 that are from each each person in sender/recipient list 221 is calculated.
The result is a name/message number pair list 407 of pairs of "person name"
and "number of messages". Finally, list 407 is sorted according to "number of messages" . The 20 names with the highest number of messages in this list are then added to the list of candidates.
After the list of candidates has been approved by the user, mail filter 109 makes a recipient specifies 121 and adds it to the email message. Recipient specifies 121 contains a recipient type request 121 which specifies that an expert is being requested and expertise description 401 is used as recipient description 125.
X15997.3 The message travels through the network and arrives at the computer systems(s) of the recipients. Each recipient mail filter 109 notes recipient specifies 121 specifying that an expert is being requested, removes the e-mail message from the incoming mail stream, and processes it as follows:
First, the words in expertise description 401 contained in the message's recipient specifies 121 are matched against the recipient's user expertise list 301. If the words appear in list 301, then mail filter 109 assumes that this request is appropriate for the recipient to see.
If the words in the phrase do not match against the contents of user expertise list 301, mail filter 109 uses user files inverted index file 305 to match the phrase against the contents of all of the recipient's files which are indexed in file 305. This matching can be efficiently performed using the program "GLIMPSE" mentioned above. If the number of matches is greater then a threshold number (e.g., more than 10 matches), the recipient's mail filter 109 determines that this request is likely to be appropriate for the recipient.
If the recipient's mail filter thus determines in either way that the message is appropriate, it uses user mail interface 117 to make the the message appear on the recipient's computer screen. The recipient is then given the option of (i) responding affirmatively back to the sender; (ii) responding negatively back to the sender; or (iii) referring the request to someone else. If this final option is selected, the recipient's mail filter 109 creates a list of candidate recipients as described above and the process is repeated.
As is apparent from the foregoing description, the preferred embodiment of the expertise locator increases its efficiency by using two-stage correspon-dent models 111 and user models 113. The first stage is the explicit descrip-tions of expertise contained in colleague list 201 and user expertise list 301;
the second stage is the inverted indexes: inverted index 213 into email file 209 and inverted index 305 into the the user's text files. The algorithms first use the expertise lists 201 and 301, and then they may in addition use the inverted indexes.
Example II: Enhanced Yellow Page Service The general techniques described above can be applied to many different kinds of tasks. The general approach is useful when the following conditions hold:
1. You wish to contact a large number of people, without necessarily broadcasting messages to everyone in the world. In the expertise location example, the user agent helped determine a preliminary list of candidates bred on a matching scheme. Other ways of determining whom to send the message to are also useful. In the example below, the recipients are simply taken to be a fixed list of the sender's friends and colleagues.
2. You want the message you send to only be seen by people to whom is it very likely to relevant, in order to avoid being disruptive. To that end, you want the message you send to explicitly indicate the conditions under which which it should be taken to be relevant. Note that the computation of relevancy may rely on information that is private to the recipient. In the previous example, the sender indicated the general conditions of relevancy by recipient type field 123 (thus indicating the general kind of processing to be performed by the recipient's mail filter 109) and the words in recipient description field 125 describing the kind of expertise required (thus providing the parameters to that processing). Another way of saying this is that the sender pro-actively determines the general manner in which the message is to be em filtered. Note that this is difFerent from earlier work on mail filtering, which always assumes that the recipient of a message is completely responsible for establishing the conditions for filtering (if any), and the sender is completely "passive" with regard to filtering.
We illustrate these core points with the following "Enhanced Yellow Page"
service. The basic idea is to provide a service that assists people in obtain ing one or more personal recommendations about a professional service or business. The system would work as follows.
A customer contacts the Enhanced Yellow Page Service (EYPS) asking for a number of a particular service (e.g., a flower delivery service, an autobody shop, a roofer, etc.). The contact with the EYPS could be made by many possible means of communication, including telephone, an on-line service, an Internet Mosaic/HTTP server, or electronic mail; alternatively, the EYPS
software and directory could even be distributed to users and run entirely on their personal computers.
The EYPS gives one or more possible numbers. The customer can then ask the EYPS to help in obtaining one or more personal recommendations about the service or business.
To obtain the recommendations, the EYPS first considers people from a list of friends or colleagues of the customer. (One way to obtain this list is by simply asking the customer to register friends, family, or colleagues but there are also less intrusive ways of doing this, such as by keeping track of people with whom the customer frequently communicates.) Now, the key idea is that the EYPS does not simply contact every person on the list, but rather only contacts those people that have dealt with the particular service or business number in the last couple of months. There are at least two ways in which this kind of "sender pro-active filtering" can be done:
1. The EYPS contacts mail filter 109 for each friend or colleague, in-dicating the name and telephone number for the service for which a rec-ommendation is desired. Mail filters 109 that have been trusted with their owner's telephone records and/or records of business transactions can deter-mine whether their owner has dealt with that company. If so, they pass the request on to the owner.
2. If the EYPS has direct access to the telephone records of the friends and colleagues (which is the case ~if the EYPS is implemented by a program running in a long-distance network itself ), then it checks the phone records itself to determine the list friends and colleagues that have called that com-pany.
Thus, instead bothering a large group of people, there is a careful screen-ing to ensure that only those are contacted who have had some recent dealings with the particular service or business. There are various ways of how the EYPS can complete the process. The least intrusive way would be to sim-ply leave a message with some of the selected people saying "Mr. or Ms.
X would be interested in any opinion or recommendation about service Y.
Please contact X at or leave message at number Z. This request expires at midnight."
Note that this kind of "pro-active" mail filtering can also be implemented by having the user send a message directly to someone's mail filter 109. The message header would include a directive saying "pass on to user if he or she has contacted service X at least twice in the last three months." Upon receipt of the message, mail filter 109 will now filter the message based on the included directive. Again, note the difference with the current forms of mail-filtering, where filtering is under complete control of the recipient, and the sender does not give direct instructions to the filtering program.
Such a system naturally raises many privacy issues that can be addressed.
For example, you may not necessarily let the person seeking the recommenda-tion know who gets the request-for-advice message. That way, people would not feel obliged to respond. Also, the identify of the requester could be pro-tected by simply having a message saying "A friend would like an opinion or recommendation about service Y." In that case the EYPS would only reveal the identity of the requester once the recipient agrees to respond.
Conclusion The foregoing Detailed Description has disclosed to those skilled in the com-puter and networking arts how non-address recipient information in an e-mail message and a mail filter which includes a model of the recipient may be used to reduce the amount of junk e-mail received by the recipient and how the non-address recipient information and a mail filter which includes models of the sender's correspondents may be used to reduce the amount of e-mail sent by a user. The Detailed Description has further disclosed how the above tech-niques may be used to construct an expertise locator and has disclosed the best mode presently known to the inventors for implementing the expertise locator.
It will be immediately apparent to those skilled in the computer and networking arts that the principles of the invention may be used in any situation where a mail filter has access to information which enables it to respond to non-address information about the potential recipients of an e-mail message. It will be further apparent that many techniques may be used to construct models of the correspondents and recipients for use by the mail filters. The models may be simple lists of keywords, they may be inverted files, they may be data bases, or they may be any other arrangement of data which permits the mail filter to determine from the model and the non-address information whether the potential recipient should actually receive the message. It will further be apparent to those skilled in the art that the location of the mail filter in the network is a matter of design choice.
Filters which are located on the same computer system as the recipient have better access to recipient information, while those which are located closer to the sender are more efficient at reducing the total amount of network traffic.
2p All of the above being the case, the foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the Detailed Description, but rather from the claims as in-terpreted according to the full breadth permitted by the law.
There are inherent problems with both general approaches to obtaining information. It has often been noted that as the world of online information sources expands, the "ask a program" approach suffers from the problem of knowing where to look. For example, the Mosaic system overcomes many of the technical problems in accessing a wide variety of information on the Internet, by automatically handling the low-level details of different commu-nication protocols. It is easy and entertaining to browse through an enormous hypermedia space. However, finding an answer to a specific question using Mosaic tends to be slow and frustrating, and often results in failure. One response to this problem has been the attempt to design systems that incor-porate knowledge about the location of information, such as the Information Manifold project (by T. Kirk, A. Levy, and D. Srivastava, of AT&T Bell Labs). However, a deeper problem remains, that no solution based solely on building a better search-engine can address. This is the fact that much valuable information is simply not online, but only exists in people's heads.
Furthermore, there are economic, social, and political reasons that much valuable information will never be made publicly accessible on the Internet or any other network. Indeed, part of the value of a piece of information resides in the degree to which it is not easily accessible.
In any large organization, determining who is an expert on a particular topic is a crucial problem. The need for expertise location ranges from in-formal situations, such as where I might need to find an expert on LaTex macros to help fix a typesetting problem in a paper I'm writing, to formal construction of project teams to meet business needs. The range of expertise specifications may range from the generic ( "who knows about logic program-ming?" ) to the highly specific ( "who knows how to modify the interrupt vector handling microcode in the reboot module of the XZY999 processor?" ).
Online directories of expertise rarely exist, and when they do, the infor mation they contain is certain to be out of date and incomplete. In fact, expertise needs are potentially so specific that it is simply impossible to de termine a comprehensive set of categories in advance. Expertise location is therefore generally an "ask a person" task, with all the problems associated with that approach outlined above.
Let us consider for a moment how expertise location actually works when it is successful. In a typical case I contact a small set of colleagues whom I think might be familiar with the topic. Because each person knows me personally, they are quite likely to respond. Usually none of them is exactly the person I want; however, they can refer me to someone they know who might be. After following a chain of referrals a few layers deep I finally find the person I want.
Note that in this successful scenario I needed to walk a fine line between contacting too few people (and thus not finding the true expert) and con-tacting too many (and eventually making a pest of myself). Even in the end I might wonder if I might not have found even a better expert if only I could have cast the net a bit wider. I may have had dif&culty bringing to mind those people I do know personally who have some expertise in the desired area. If only all of my colleagues employed endlessly patient assistants that I
could have contacted initially, who would have known something about their bosses' areas of expertise, and who could have answered my initial queries without disturbing everyone...
A
Now let us consider how mail filters could be used to augment the expert location process. Each person's mail filter would create a model of that person's areas of interest. This model would be created automatically by using information retrieval (IR) techniques (such as inverted indexes) on all the documents created and received by the user. The user model could be quite large and detailed, and would be private to the user, that is, not stored in a central database. The mail filter would also create a much more coarse-grained model of my contacts by applying similar techniques to all the electronic mail that I exchange with each person.
When I have an expertise location need, I present the problem to my mail filter as an unstructured text description. Again using IR techniques, my mail filter selects a medium-to-large set of my contacts to whom the query may be relevant. It then broadcasts the query, not to the people themselves, but to their mail filters. Upon receipt of the question, each mail filter checks if its owner's user model does indeed provide a good match. If there is a good match, the mail filter presents my request to its owner. If the owner's model does not match, but the model of one of the owner's contacts does, then the mail filter can ask the owner if it can provide a referral. Finally, if there is no match at all, the query is silently logged and deleted. A great deal of flexibility can be built into each mail filter, depending upon its owner's preferences. For example, I might allow automatic referrals to be given to requests that come from my closest colleagues.
This system provides several benefits over either sending personal e-mail to everyone in order to find an expert or using netnews to find the expert.
First, it is largely passive on the part of the recipients - they do not need to -~- 21 5 9 9 7 3 be reading netnews and wading through dozens of articles. Second, queries are broadcast in a focused manner to those who are at least somewhat likely to find them of interest. Third, users are shielded from seeing a large number of completely irrelevant messages; each mail filter 109 may process dozens of messages for every one the user sees. Finally, messages that a user does see do not come from "out of the blue", but rather are tagged with a chain of referrals from colleague to colleague.
One reason to believe that the system just described would be useful in practice is that it basically models the manner in which expertise location actually works now (D. Krackhardt and J. R. Hanson, "Informal Networks: The Company Behind the Chart", Harvard Business Review, July-August 1993), while allowing more people to be contacted without causing disruption and disturbance.
Implementation of an Expertise Locator A presently-preferred embodiment of the expertise locator has been implemented using network agents described in Coen, et al., Network Agents, European Patent EP
669733. In the implementation, mail filter 109 is a component of a user agent which handles e-mail messages for its user. Mail filters 109 are written in the programming language Visual Basic, and run on a standard personal computer. Interactive user mail interface 117 presents the expertise locator in mail filter 109 to the user as an anthropomorphic "talking head" that appears in a window on the computer screen. All the computers running mail filters 109 are networked (currently A
using the protocol TCP/IP), and can exchange electronic mail with each other and with any person. A mail filter 109 can also invoke other programs to perform various subtasks.
Each mail filter 109 has access to two sets of data base files. The first set, shown in FIG. 2, implements correspondent models 111; the second set, shown in FIG. 3, implements user model 113. Each of the data base files in the two sets is specific to and owned by the individual user of mail filter 109.
It is important to note that we do not assume that these files can be directly accessed by anyone other than the user and mail filter 109.
Correspondent models 111 contains the following five files:
~ Colleague list 201 which contains entries 203 for some of the user's colleagues. Each entry 203 contains an identification 205 for the col-league and each a list of keywords 207 describing the colleague's areas of expertise.
~ An Email file 209 which contains all of the email 211(O..n) that the user has sent and received for a substantial period of time: typically, the past year or several years.
~ An Email inverted index file 213 that has an entry 215 for each word that appears in any email message. Entry 215 contains a word 217 and a list of the numbers of the messages in email file 209 that contain that word. This kind of file can be generated using standard information retrieval algorithms, such as those described in (G. Salton, Automatic Text Processing, Addison-Wesley 1989).
~ A sender/recipient list file 221 that has an entry 223 for each message in email file 209. The entry contains the identifier of the sender of the corresponding message (if other than the user) or the identifier of the recipient of the corresponding message (if sent by the user).
FIG. 3 shows the data base files used to implement user model 113.
~ User expertise list 301 is a file containing a list of keywords that describe some of the user's own areas of expertise.
~ User files inverted index 305 is a file containing an inverted index of text files in the user's directory. That is, for every word that appears in any file the user has stored on the computer, this file contains a list of the names of the files containing that word.
In the preferred embodiment, colleague list 201 and user expertise list 301 are created by mail filter 109 in interaction with user 105(n); the inverted index files 213 and user files inverted index 305 are created automatically by mail filter 109. This kind of very large inverted index can be quickly created and searched by the program "glimpse" (U. Manber and S. Wu, "GLIMPSE: A
Tool to Search Through Entire File Systems," Usenix Winter 199 Technical Conference, San Francisco (January 1994), pp. 23-32). In making inverted list 305, GLIMPSE uses a UNIX operating system (UNIX is a trademark of XOPEN) utility which determines whether a file is a text file. In addition, the user can specify to GLIMPSE which directories of files or individual files are to be indexed.
A user begins the process of locating an expert in a topic by clicking on the window for mail filter 109 and typing a phrase that describes the general 21599?3 kind of request (such as, "I need to locate an expert"). Mail filter 109 then prompts the user for a phrase describing the area of expertise. Once this is done, mail filter 109 generates and presents for approval a list of suggested candidates for receiving the request.
The list of candidates is generated by combining names from two sources.
First, names are added that appear in colleague list 201, such that the words that appear in the phrase describing the expertise request appear in the list of keywords 207 associated with name 205.
Second, names are added that result from the following computation.
First, for each word that appears in the expertise request, mail filter 109 retrieves from email inverted index file 213 a list of messages 403(O..n) (FIG.
4) containing that word. Next, the intersection of the lists is computed, generating a list of messages 405 each of which appears in every one of the previous lists. Next, list of messages 405 is compared against sender/recipient list file 221, and the total number of messages that appear in list of messages 405 that are from each each person in sender/recipient list 221 is calculated.
The result is a name/message number pair list 407 of pairs of "person name"
and "number of messages". Finally, list 407 is sorted according to "number of messages" . The 20 names with the highest number of messages in this list are then added to the list of candidates.
After the list of candidates has been approved by the user, mail filter 109 makes a recipient specifies 121 and adds it to the email message. Recipient specifies 121 contains a recipient type request 121 which specifies that an expert is being requested and expertise description 401 is used as recipient description 125.
X15997.3 The message travels through the network and arrives at the computer systems(s) of the recipients. Each recipient mail filter 109 notes recipient specifies 121 specifying that an expert is being requested, removes the e-mail message from the incoming mail stream, and processes it as follows:
First, the words in expertise description 401 contained in the message's recipient specifies 121 are matched against the recipient's user expertise list 301. If the words appear in list 301, then mail filter 109 assumes that this request is appropriate for the recipient to see.
If the words in the phrase do not match against the contents of user expertise list 301, mail filter 109 uses user files inverted index file 305 to match the phrase against the contents of all of the recipient's files which are indexed in file 305. This matching can be efficiently performed using the program "GLIMPSE" mentioned above. If the number of matches is greater then a threshold number (e.g., more than 10 matches), the recipient's mail filter 109 determines that this request is likely to be appropriate for the recipient.
If the recipient's mail filter thus determines in either way that the message is appropriate, it uses user mail interface 117 to make the the message appear on the recipient's computer screen. The recipient is then given the option of (i) responding affirmatively back to the sender; (ii) responding negatively back to the sender; or (iii) referring the request to someone else. If this final option is selected, the recipient's mail filter 109 creates a list of candidate recipients as described above and the process is repeated.
As is apparent from the foregoing description, the preferred embodiment of the expertise locator increases its efficiency by using two-stage correspon-dent models 111 and user models 113. The first stage is the explicit descrip-tions of expertise contained in colleague list 201 and user expertise list 301;
the second stage is the inverted indexes: inverted index 213 into email file 209 and inverted index 305 into the the user's text files. The algorithms first use the expertise lists 201 and 301, and then they may in addition use the inverted indexes.
Example II: Enhanced Yellow Page Service The general techniques described above can be applied to many different kinds of tasks. The general approach is useful when the following conditions hold:
1. You wish to contact a large number of people, without necessarily broadcasting messages to everyone in the world. In the expertise location example, the user agent helped determine a preliminary list of candidates bred on a matching scheme. Other ways of determining whom to send the message to are also useful. In the example below, the recipients are simply taken to be a fixed list of the sender's friends and colleagues.
2. You want the message you send to only be seen by people to whom is it very likely to relevant, in order to avoid being disruptive. To that end, you want the message you send to explicitly indicate the conditions under which which it should be taken to be relevant. Note that the computation of relevancy may rely on information that is private to the recipient. In the previous example, the sender indicated the general conditions of relevancy by recipient type field 123 (thus indicating the general kind of processing to be performed by the recipient's mail filter 109) and the words in recipient description field 125 describing the kind of expertise required (thus providing the parameters to that processing). Another way of saying this is that the sender pro-actively determines the general manner in which the message is to be em filtered. Note that this is difFerent from earlier work on mail filtering, which always assumes that the recipient of a message is completely responsible for establishing the conditions for filtering (if any), and the sender is completely "passive" with regard to filtering.
We illustrate these core points with the following "Enhanced Yellow Page"
service. The basic idea is to provide a service that assists people in obtain ing one or more personal recommendations about a professional service or business. The system would work as follows.
A customer contacts the Enhanced Yellow Page Service (EYPS) asking for a number of a particular service (e.g., a flower delivery service, an autobody shop, a roofer, etc.). The contact with the EYPS could be made by many possible means of communication, including telephone, an on-line service, an Internet Mosaic/HTTP server, or electronic mail; alternatively, the EYPS
software and directory could even be distributed to users and run entirely on their personal computers.
The EYPS gives one or more possible numbers. The customer can then ask the EYPS to help in obtaining one or more personal recommendations about the service or business.
To obtain the recommendations, the EYPS first considers people from a list of friends or colleagues of the customer. (One way to obtain this list is by simply asking the customer to register friends, family, or colleagues but there are also less intrusive ways of doing this, such as by keeping track of people with whom the customer frequently communicates.) Now, the key idea is that the EYPS does not simply contact every person on the list, but rather only contacts those people that have dealt with the particular service or business number in the last couple of months. There are at least two ways in which this kind of "sender pro-active filtering" can be done:
1. The EYPS contacts mail filter 109 for each friend or colleague, in-dicating the name and telephone number for the service for which a rec-ommendation is desired. Mail filters 109 that have been trusted with their owner's telephone records and/or records of business transactions can deter-mine whether their owner has dealt with that company. If so, they pass the request on to the owner.
2. If the EYPS has direct access to the telephone records of the friends and colleagues (which is the case ~if the EYPS is implemented by a program running in a long-distance network itself ), then it checks the phone records itself to determine the list friends and colleagues that have called that com-pany.
Thus, instead bothering a large group of people, there is a careful screen-ing to ensure that only those are contacted who have had some recent dealings with the particular service or business. There are various ways of how the EYPS can complete the process. The least intrusive way would be to sim-ply leave a message with some of the selected people saying "Mr. or Ms.
X would be interested in any opinion or recommendation about service Y.
Please contact X at or leave message at number Z. This request expires at midnight."
Note that this kind of "pro-active" mail filtering can also be implemented by having the user send a message directly to someone's mail filter 109. The message header would include a directive saying "pass on to user if he or she has contacted service X at least twice in the last three months." Upon receipt of the message, mail filter 109 will now filter the message based on the included directive. Again, note the difference with the current forms of mail-filtering, where filtering is under complete control of the recipient, and the sender does not give direct instructions to the filtering program.
Such a system naturally raises many privacy issues that can be addressed.
For example, you may not necessarily let the person seeking the recommenda-tion know who gets the request-for-advice message. That way, people would not feel obliged to respond. Also, the identify of the requester could be pro-tected by simply having a message saying "A friend would like an opinion or recommendation about service Y." In that case the EYPS would only reveal the identity of the requester once the recipient agrees to respond.
Conclusion The foregoing Detailed Description has disclosed to those skilled in the com-puter and networking arts how non-address recipient information in an e-mail message and a mail filter which includes a model of the recipient may be used to reduce the amount of junk e-mail received by the recipient and how the non-address recipient information and a mail filter which includes models of the sender's correspondents may be used to reduce the amount of e-mail sent by a user. The Detailed Description has further disclosed how the above tech-niques may be used to construct an expertise locator and has disclosed the best mode presently known to the inventors for implementing the expertise locator.
It will be immediately apparent to those skilled in the computer and networking arts that the principles of the invention may be used in any situation where a mail filter has access to information which enables it to respond to non-address information about the potential recipients of an e-mail message. It will be further apparent that many techniques may be used to construct models of the correspondents and recipients for use by the mail filters. The models may be simple lists of keywords, they may be inverted files, they may be data bases, or they may be any other arrangement of data which permits the mail filter to determine from the model and the non-address information whether the potential recipient should actually receive the message. It will further be apparent to those skilled in the art that the location of the mail filter in the network is a matter of design choice.
Filters which are located on the same computer system as the recipient have better access to recipient information, while those which are located closer to the sender are more efficient at reducing the total amount of network traffic.
2p All of the above being the case, the foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the Detailed Description, but rather from the claims as in-terpreted according to the full breadth permitted by the law.
Claims (16)
1. Apparatus for automatically limiting the recipients of a message sent via a mail system implemented in a computer system, the apparatus comprising:
recipient specifying means in the message which uses non-address information to specify the recipients of the message;
message filtering means in the computer system having access to recipient information contained therein about at least one potential recipient and including means responsive to the non-address information and to the recipient information for providing the message to the at least one potential recipient if the non-address information and the recipient information together indicate that the at least one potential recipient is to receive the message; and means, in the message filtering means, for sending a referral message to a source of the message when the message filtering means provides the message to the at least one potential recipient.
recipient specifying means in the message which uses non-address information to specify the recipients of the message;
message filtering means in the computer system having access to recipient information contained therein about at least one potential recipient and including means responsive to the non-address information and to the recipient information for providing the message to the at least one potential recipient if the non-address information and the recipient information together indicate that the at least one potential recipient is to receive the message; and means, in the message filtering means, for sending a referral message to a source of the message when the message filtering means provides the message to the at least one potential recipient.
2. The apparatus set forth in claim 1 wherein:
the referral message contains an identification of the at least one potential recipient.
the referral message contains an identification of the at least one potential recipient.
3. The apparatus set forth in claim 1 wherein:
the message is received by a plurality of users;
the message includes information specifying the users who received the message; and the referral message further contains the information specifying the users who received the message.
the message is received by a plurality of users;
the message includes information specifying the users who received the message; and the referral message further contains the information specifying the users who received the message.
4. An arrangement for locating expertise in a messaging system implemented in a computer system, comprising:
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the.
third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee;
fifth means in the computer system, for determining expertise of contacts of the addressee;
sixth means responsive to a determination that the indicated expertise does not match the determined expertise of the addressee, for determining whether the indicated expertise matches the expertise of any said contacts determined by the fifth means; and seventh means responsive to a determination by the sixth means that the indicated expertise matches the determined expertise of a contact, for sending the message to that contact.
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the.
third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee;
fifth means in the computer system, for determining expertise of contacts of the addressee;
sixth means responsive to a determination that the indicated expertise does not match the determined expertise of the addressee, for determining whether the indicated expertise matches the expertise of any said contacts determined by the fifth means; and seventh means responsive to a determination by the sixth means that the indicated expertise matches the determined expertise of a contact, for sending the message to that contact.
5. The arrangement of claim 4 wherein:
the second, third, and fourth means are associated with the addressee.
the second, third, and fourth means are associated with the addressee.
6. The arrangement of claim 4 wherein:
the fifth and sixth means are associated with the addressee.
the fifth and sixth means are associated with the addressee.
7. The arrangement of claim 4 further comprising:
eighth means responsive to a determination by the sixth means that the indicated expertise does not match the determined expertise of any contact, for discarding the message.
eighth means responsive to a determination by the sixth means that the indicated expertise does not match the determined expertise of any contact, for discarding the message.
8. The arrangement of claim 7 wherein:
the eighth means are associated with the addressee.
the eighth means are associated with the addressee.
9. The arrangement of claim 4 wherein:
the fifth means comprise means for analyzing messages exchanged by the sender with the contacts to determine therefrom the expertise of the contacts.
the fifth means comprise means for analyzing messages exchanged by the sender with the contacts to determine therefrom the expertise of the contacts.
10. The arrangement of claim 4 further comprising:
eighth means in the computer system responsive to the sixth means determining that the indicated expertise matches the determined expertise of a contact, for including referral information in the message to indicate that the message is being sent from the addressee to that contact.
eighth means in the computer system responsive to the sixth means determining that the indicated expertise matches the determined expertise of a contact, for including referral information in the message to indicate that the message is being sent from the addressee to that contact.
11. The arrangement of claim 4 wherein:
the first means comprise means for conveying a list of keywords.
the first means comprise means for conveying a list of keywords.
12. An arrangement for locating expertise in a messaging system implemented in a computer system, comprising:
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for analyzing files of an addressee of the message to determine therefrom expertise of the addressee;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means; and fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee.
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for analyzing files of an addressee of the message to determine therefrom expertise of the addressee;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means; and fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee.
13. An arrangement for locating expertise in a messaging system implemented in a computer system, comprising:
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means is in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee;
fifth means in the computer system for analyzing messages exchanged by the sender with potential recipients of the message to determine therefrom the expertise of the potential recipients; and sixth means in the computer system responsive to generation of the message by the sender, for selecting addressees of the message from the potential recipients by matching the expertise sought by the sender with the expertise of the potential recipients determined by the fifth means.
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means is in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee;
fifth means in the computer system for analyzing messages exchanged by the sender with potential recipients of the message to determine therefrom the expertise of the potential recipients; and sixth means in the computer system responsive to generation of the message by the sender, for selecting addressees of the message from the potential recipients by matching the expertise sought by the sender with the expertise of the potential recipients determined by the fifth means.
14. The arrangement of claim 13 further comprising:
messaging means for sending the message to the selected addressees of the message.
messaging means for sending the message to the selected addressees of the message.
15. The arrangement of claim 13 wherein:
the fifth and sixth means are associated with the sender.
the fifth and sixth means are associated with the sender.
16. An arrangement for locating expertise in a messaging system implemented in a computer system, comprising:
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee; and fifth means in the computer system responsive to the fourth means providing the message to the addressee, for sending a referral message to the sender to inform the sender that the message was provided to the addressee.
first means, included in a message, for indicating, via non-address information, expertise sought by a sender of the message;
second means in the computer system, for determining expertise of an addressee of the message;
third means in the computer system responsive to receipt of the message, for determining whether the expertise indicated by the first means matches the expertise of the addressee determined by the second means;
fourth means in the computer system responsive to a determination by the third means that the indicated expertise matches the determined expertise, for providing the message to the addressee, and responsive to a determination by the third means that the indicated expertise does not match the determined expertise, for preventing the message from being provided to the addressee; and fifth means in the computer system responsive to the fourth means providing the message to the addressee, for sending a referral message to the sender to inform the sender that the message was provided to the addressee.
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Families Citing this family (511)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5822527A (en) * | 1990-05-04 | 1998-10-13 | Digital Equipment Corporation | Method and apparatus for information stream filtration using tagged information access and action registration |
US6564321B2 (en) * | 1995-04-28 | 2003-05-13 | Bobo Ii Charles R | Systems and methods for storing, delivering, and managing messages |
US5864683A (en) * | 1994-10-12 | 1999-01-26 | Secure Computing Corporartion | System for providing secure internetwork by connecting type enforcing secure computers to external network for limiting access to data based on user and process access rights |
WO1996035994A1 (en) * | 1995-05-08 | 1996-11-14 | Compuserve Incorporated | Rules based electronic message management system |
US7272639B1 (en) | 1995-06-07 | 2007-09-18 | Soverain Software Llc | Internet server access control and monitoring systems |
US5826269A (en) * | 1995-06-21 | 1998-10-20 | Microsoft Corporation | Electronic mail interface for a network server |
US5774670A (en) | 1995-10-06 | 1998-06-30 | Netscape Communications Corporation | Persistent client state in a hypertext transfer protocol based client-server system |
US6021428A (en) * | 1997-09-15 | 2000-02-01 | Genesys Telecommunications Laboratories, Inc. | Apparatus and method in improving e-mail routing in an internet protocol network telephony call-in-center |
US5958006A (en) * | 1995-11-13 | 1999-09-28 | Motorola, Inc. | Method and apparatus for communicating summarized data |
US5771355A (en) * | 1995-12-21 | 1998-06-23 | Intel Corporation | Transmitting electronic mail by either reference or value at file-replication points to minimize costs |
US6084952A (en) * | 1996-01-18 | 2000-07-04 | Pocketscience, Inc. | System and method for communicating electronic messages over a telephone network using acoustical coupling |
US5913024A (en) | 1996-02-09 | 1999-06-15 | Secure Computing Corporation | Secure server utilizing separate protocol stacks |
US5918018A (en) | 1996-02-09 | 1999-06-29 | Secure Computing Corporation | System and method for achieving network separation |
JPH09219722A (en) * | 1996-02-13 | 1997-08-19 | Hitachi Ltd | Communication system |
US5826022A (en) * | 1996-04-05 | 1998-10-20 | Sun Microsystems, Inc. | Method and apparatus for receiving electronic mail |
US5794233A (en) * | 1996-04-09 | 1998-08-11 | Rubinstein; Seymour I. | Browse by prompted keyword phrases |
US5742769A (en) * | 1996-05-06 | 1998-04-21 | Banyan Systems, Inc. | Directory with options for access to and display of email addresses |
US5884033A (en) * | 1996-05-15 | 1999-03-16 | Spyglass, Inc. | Internet filtering system for filtering data transferred over the internet utilizing immediate and deferred filtering actions |
US6453327B1 (en) * | 1996-06-10 | 2002-09-17 | Sun Microsystems, Inc. | Method and apparatus for identifying and discarding junk electronic mail |
AU725370C (en) * | 1996-06-18 | 2003-01-02 | Cranberry Properties, Llc | Integrated voice, facsimile and electronic mail messaging system |
US5819269A (en) * | 1996-06-21 | 1998-10-06 | Robert G. Uomini | Dynamic subgrouping in a news network |
US5835722A (en) * | 1996-06-27 | 1998-11-10 | Logon Data Corporation | System to control content and prohibit certain interactive attempts by a person using a personal computer |
US6035104A (en) * | 1996-06-28 | 2000-03-07 | Data Link Systems Corp. | Method and apparatus for managing electronic documents by alerting a subscriber at a destination other than the primary destination |
US5781857A (en) * | 1996-06-28 | 1998-07-14 | Motorola, Inc. | Method of establishing an email monitor responsive to a wireless communications system user |
US5862223A (en) | 1996-07-24 | 1999-01-19 | Walker Asset Management Limited Partnership | Method and apparatus for a cryptographically-assisted commercial network system designed to facilitate and support expert-based commerce |
ATE536588T1 (en) * | 1996-07-25 | 2011-12-15 | Xcelera Inc | WEB SERVER SYSTEM WITH PRIMARY AND SECONDARY SERVERS |
US6301608B1 (en) | 1996-08-14 | 2001-10-09 | At&T Corp. | Method and apparatus providing personalized mailbox filters |
US6584498B2 (en) | 1996-09-13 | 2003-06-24 | Planet Web, Inc. | Dynamic preloading of web pages |
US6377978B1 (en) * | 1996-09-13 | 2002-04-23 | Planetweb, Inc. | Dynamic downloading of hypertext electronic mail messages |
US6003084A (en) * | 1996-09-13 | 1999-12-14 | Secure Computing Corporation | Secure network proxy for connecting entities |
US5950195A (en) * | 1996-09-18 | 1999-09-07 | Secure Computing Corporation | Generalized security policy management system and method |
US6144934A (en) * | 1996-09-18 | 2000-11-07 | Secure Computing Corporation | Binary filter using pattern recognition |
US5983350A (en) * | 1996-09-18 | 1999-11-09 | Secure Computing Corporation | Secure firewall supporting different levels of authentication based on address or encryption status |
US6072942A (en) * | 1996-09-18 | 2000-06-06 | Secure Computing Corporation | System and method of electronic mail filtering using interconnected nodes |
GB2317793B (en) * | 1996-09-18 | 2001-03-28 | Secure Computing Corp | System and method of electronic mail filtering |
US5978837A (en) * | 1996-09-27 | 1999-11-02 | At&T Corp. | Intelligent pager for remotely managing E-Mail messages |
US5809250A (en) * | 1996-10-23 | 1998-09-15 | Intel Corporation | Methods for creating and sharing replayable modules representive of Web browsing session |
US5796948A (en) * | 1996-11-12 | 1998-08-18 | Cohen; Elliot D. | Offensive message interceptor for computers |
US5915087A (en) * | 1996-12-12 | 1999-06-22 | Secure Computing Corporation | Transparent security proxy for unreliable message exchange protocols |
JP3841233B2 (en) * | 1996-12-18 | 2006-11-01 | ソニー株式会社 | Information processing apparatus and information processing method |
US6146026A (en) * | 1996-12-27 | 2000-11-14 | Canon Kabushiki Kaisha | System and apparatus for selectively publishing electronic-mail |
US7031442B1 (en) | 1997-02-10 | 2006-04-18 | Genesys Telecommunications Laboratories, Inc. | Methods and apparatus for personal routing in computer-simulated telephony |
US6029171A (en) | 1997-02-10 | 2000-02-22 | Actioneer, Inc. | Method and apparatus for group action processing between users of a collaboration system |
US6104802A (en) | 1997-02-10 | 2000-08-15 | Genesys Telecommunications Laboratories, Inc. | In-band signaling for routing |
US6480600B1 (en) | 1997-02-10 | 2002-11-12 | Genesys Telecommunications Laboratories, Inc. | Call and data correspondence in a call-in center employing virtual restructuring for computer telephony integrated functionality |
DE19809231A1 (en) * | 1997-03-04 | 1998-09-17 | Talkway Inc | System for improved discussion technologies |
US6185603B1 (en) * | 1997-03-13 | 2001-02-06 | At&T Corp. | Method and system for delivery of e-mail and alerting messages |
US6732154B1 (en) * | 1997-03-18 | 2004-05-04 | Paratran Corporation | Distribution limiter for network messaging |
JPH10275119A (en) * | 1997-03-31 | 1998-10-13 | Hitachi Software Eng Co Ltd | Electronic mail system |
JP3790602B2 (en) * | 1997-04-25 | 2006-06-28 | 富士ゼロックス株式会社 | Information sharing device |
US6021427A (en) * | 1997-05-22 | 2000-02-01 | International Business Machines Corporation | Method and system for preventing routing maelstrom loops of automatically routed electronic mail |
US6185551B1 (en) | 1997-06-16 | 2001-02-06 | Digital Equipment Corporation | Web-based electronic mail service apparatus and method using full text and label indexing |
US6092101A (en) * | 1997-06-16 | 2000-07-18 | Digital Equipment Corporation | Method for filtering mail messages for a plurality of client computers connected to a mail service system |
US6023700A (en) * | 1997-06-17 | 2000-02-08 | Cranberry Properties, Llc | Electronic mail distribution system for integrated electronic communication |
US6128739A (en) * | 1997-06-17 | 2000-10-03 | Micron Electronics, Inc. | Apparatus for locating a stolen electronic device using electronic mail |
US6052782A (en) * | 1997-06-17 | 2000-04-18 | Micron Electronics, Inc. | Method for locating a stolen electronic device using electronic mail |
US6073142A (en) * | 1997-06-23 | 2000-06-06 | Park City Group | Automated post office based rule analysis of e-mail messages and other data objects for controlled distribution in network environments |
US6067569A (en) * | 1997-07-10 | 2000-05-23 | Microsoft Corporation | Fast-forwarding and filtering of network packets in a computer system |
US6615241B1 (en) * | 1997-07-18 | 2003-09-02 | Net Exchange, Llc | Correspondent-centric management email system uses message-correspondent relationship data table for automatically linking a single stored message with its correspondents |
US7127741B2 (en) | 1998-11-03 | 2006-10-24 | Tumbleweed Communications Corp. | Method and system for e-mail message transmission |
US7162738B2 (en) | 1998-11-03 | 2007-01-09 | Tumbleweed Communications Corp. | E-mail firewall with stored key encryption/decryption |
ATE444614T1 (en) * | 1997-07-24 | 2009-10-15 | Axway Inc | EMAIL FIREWALL |
US20050081059A1 (en) * | 1997-07-24 | 2005-04-14 | Bandini Jean-Christophe Denis | Method and system for e-mail filtering |
US7117358B2 (en) * | 1997-07-24 | 2006-10-03 | Tumbleweed Communications Corp. | Method and system for filtering communication |
US6898627B1 (en) * | 1997-07-25 | 2005-05-24 | Canon Kabushiki Kaisha | Communication device having the capability of performing information exchange between a facsimile medium and an electronic information medium such as an e-mail medium |
JP2001512862A (en) * | 1997-07-30 | 2001-08-28 | ブリティッシュ・テレコミュニケーションズ・パブリック・リミテッド・カンパニー | Communication device |
US6249805B1 (en) * | 1997-08-12 | 2001-06-19 | Micron Electronics, Inc. | Method and system for filtering unauthorized electronic mail messages |
US5999967A (en) * | 1997-08-17 | 1999-12-07 | Sundsted; Todd | Electronic mail filtering by electronic stamp |
US6542923B2 (en) | 1997-08-21 | 2003-04-01 | Planet Web, Inc. | Active electronic mail |
US6564250B1 (en) | 1997-08-21 | 2003-05-13 | Planetweb, Inc. | Miniclient for internet appliance |
US7325077B1 (en) | 1997-08-21 | 2008-01-29 | Beryl Technical Assays Llc | Miniclient for internet appliance |
US6032150A (en) * | 1997-08-25 | 2000-02-29 | Planetweb, Inc. | Secure graphical objects in web documents with a program applet placed to present further information upon selected conditions |
US6199102B1 (en) | 1997-08-26 | 2001-03-06 | Christopher Alan Cobb | Method and system for filtering electronic messages |
US6678718B1 (en) | 1997-08-29 | 2004-01-13 | Aspect Communications Corporation | Method and apparatus for establishing connections |
AU8880198A (en) * | 1997-09-16 | 1999-04-05 | British Telecommunications Public Limited Company | Messaging system |
US6985943B2 (en) | 1998-09-11 | 2006-01-10 | Genesys Telecommunications Laboratories, Inc. | Method and apparatus for extended management of state and interaction of a remote knowledge worker from a contact center |
US6711611B2 (en) | 1998-09-11 | 2004-03-23 | Genesis Telecommunications Laboratories, Inc. | Method and apparatus for data-linking a mobile knowledge worker to home communication-center infrastructure |
US6266664B1 (en) * | 1997-10-01 | 2001-07-24 | Rulespace, Inc. | Method for scanning, analyzing and rating digital information content |
US6118789A (en) * | 1998-02-19 | 2000-09-12 | Micron Technology, Inc. | Method of addressing messages and communications system |
US6041326A (en) * | 1997-11-14 | 2000-03-21 | International Business Machines Corporation | Method and system in a computer network for an intelligent search engine |
USRE46528E1 (en) | 1997-11-14 | 2017-08-29 | Genesys Telecommunications Laboratories, Inc. | Implementation of call-center outbound dialing capability at a telephony network level |
US6185599B1 (en) * | 1997-11-19 | 2001-02-06 | At&T Corporation | Method of electronic bidding over networks through data tagging and data scanning |
US6219691B1 (en) * | 1997-11-19 | 2001-04-17 | At&T Corporation | Communication circulation system and method for communication in a network |
US6393465B2 (en) * | 1997-11-25 | 2002-05-21 | Nixmail Corporation | Junk electronic mail detector and eliminator |
US8412778B2 (en) * | 1997-11-25 | 2013-04-02 | Robert G. Leeds | Junk electronic mail detector and eliminator |
JP3087710B2 (en) * | 1997-11-29 | 2000-09-11 | ブラザー工業株式会社 | Facsimile machine |
US6330610B1 (en) | 1997-12-04 | 2001-12-11 | Eric E. Docter | Multi-stage data filtering system employing multiple filtering criteria |
US6023723A (en) * | 1997-12-22 | 2000-02-08 | Accepted Marketing, Inc. | Method and system for filtering unwanted junk e-mail utilizing a plurality of filtering mechanisms |
WO1999032985A1 (en) * | 1997-12-22 | 1999-07-01 | Accepted Marketing, Inc. | E-mail filter and method thereof |
US6052709A (en) * | 1997-12-23 | 2000-04-18 | Bright Light Technologies, Inc. | Apparatus and method for controlling delivery of unsolicited electronic mail |
US9900305B2 (en) * | 1998-01-12 | 2018-02-20 | Soverain Ip, Llc | Internet server access control and monitoring systems |
US5999932A (en) * | 1998-01-13 | 1999-12-07 | Bright Light Technologies, Inc. | System and method for filtering unsolicited electronic mail messages using data matching and heuristic processing |
US6782510B1 (en) | 1998-01-27 | 2004-08-24 | John N. Gross | Word checking tool for controlling the language content in documents using dictionaries with modifyable status fields |
US8060613B2 (en) * | 1998-02-10 | 2011-11-15 | Level 3 Communications, Llc | Resource invalidation in a content delivery network |
US7054935B2 (en) | 1998-02-10 | 2006-05-30 | Savvis Communications Corporation | Internet content delivery network |
US6185598B1 (en) * | 1998-02-10 | 2001-02-06 | Digital Island, Inc. | Optimized network resource location |
US7907598B2 (en) | 1998-02-17 | 2011-03-15 | Genesys Telecommunication Laboratories, Inc. | Method for implementing and executing communication center routing strategies represented in extensible markup language |
US6357010B1 (en) | 1998-02-17 | 2002-03-12 | Secure Computing Corporation | System and method for controlling access to documents stored on an internal network |
US6275476B1 (en) | 1998-02-19 | 2001-08-14 | Micron Technology, Inc. | Method of addressing messages and communications system |
US6061344A (en) | 1998-02-19 | 2000-05-09 | Micron Technology, Inc. | Method of addressing messages and communications system |
US6072801A (en) | 1998-02-19 | 2000-06-06 | Micron Technology, Inc. | Method of addressing messages, method of establishing wireless communications, and communications system |
USRE43382E1 (en) | 1998-02-19 | 2012-05-15 | Round Rock Research, Llc | Method of addressing messages and communications systems |
US6332154B2 (en) | 1998-09-11 | 2001-12-18 | Genesys Telecommunications Laboratories, Inc. | Method and apparatus for providing media-independent self-help modules within a multimedia communication-center customer interface |
US6330597B2 (en) | 1998-03-04 | 2001-12-11 | Conexant Systems, Inc. | Method and apparatus for monitoring, controlling, and configuring remote communication devices |
JP2951307B1 (en) * | 1998-03-10 | 1999-09-20 | 株式会社ガーラ | Electronic bulletin board system |
US6321336B1 (en) | 1998-03-13 | 2001-11-20 | Secure Computing Corporation | System and method for redirecting network traffic to provide secure communication |
US6453419B1 (en) | 1998-03-18 | 2002-09-17 | Secure Computing Corporation | System and method for implementing a security policy |
US6182226B1 (en) | 1998-03-18 | 2001-01-30 | Secure Computing Corporation | System and method for controlling interactions between networks |
US6073167A (en) * | 1998-03-18 | 2000-06-06 | Paratran Corporation | Distribution limiter for network messaging |
US7185332B1 (en) | 1998-03-25 | 2007-02-27 | Symantec Corporation | Multi-tiered incremental software updating |
US6609656B1 (en) | 1998-03-27 | 2003-08-26 | Micron Technology, Inc. | Method and system for identifying lost or stolen devices |
US6438580B1 (en) * | 1998-03-30 | 2002-08-20 | Electronic Data Systems Corporation | System and method for an interactive knowledgebase |
US6684211B1 (en) | 1998-04-01 | 2004-01-27 | Planetweb, Inc. | Multimedia communication and presentation |
US6751211B1 (en) | 1998-04-03 | 2004-06-15 | Aspect Communications Corporation | Method and apparatus for communicating information |
US6205432B1 (en) * | 1998-06-05 | 2001-03-20 | Creative Internet Concepts, Llc | Background advertising system |
IL124799A0 (en) * | 1998-06-07 | 1999-01-26 | Ziv Hana | E-mail prioritization |
US6247043B1 (en) * | 1998-06-11 | 2001-06-12 | International Business Machines Corporation | Apparatus, program products and methods utilizing intelligent contact management |
US6138148A (en) * | 1998-06-18 | 2000-10-24 | Sun Microsystems, Inc. | Client intermediation of server applications |
US6161130A (en) * | 1998-06-23 | 2000-12-12 | Microsoft Corporation | Technique which utilizes a probabilistic classifier to detect "junk" e-mail by automatically updating a training and re-training the classifier based on the updated training set |
US6829635B1 (en) * | 1998-07-01 | 2004-12-07 | Brent Townshend | System and method of automatically generating the criteria to identify bulk electronic mail |
US7275082B2 (en) * | 1998-07-15 | 2007-09-25 | Pang Stephen Y F | System for policing junk e-mail messages |
US6493007B1 (en) | 1998-07-15 | 2002-12-10 | Stephen Y. Pang | Method and device for removing junk e-mail messages |
US6167434A (en) * | 1998-07-15 | 2000-12-26 | Pang; Stephen Y. | Computer code for removing junk e-mail messages |
US7389413B2 (en) | 1998-07-23 | 2008-06-17 | Tumbleweed Communications Corp. | Method and system for filtering communication |
US6112227A (en) * | 1998-08-06 | 2000-08-29 | Heiner; Jeffrey Nelson | Filter-in method for reducing junk e-mail |
US6615348B1 (en) | 1999-04-16 | 2003-09-02 | Intel Corporation | Method and apparatus for an adapted digital signature |
US6356935B1 (en) | 1998-08-14 | 2002-03-12 | Xircom Wireless, Inc. | Apparatus and method for an authenticated electronic userid |
US6085321A (en) | 1998-08-14 | 2000-07-04 | Omnipoint Corporation | Unique digital signature |
US6356898B2 (en) * | 1998-08-31 | 2002-03-12 | International Business Machines Corporation | Method and system for summarizing topics of documents browsed by a user |
US7197534B2 (en) * | 1998-09-01 | 2007-03-27 | Big Fix, Inc. | Method and apparatus for inspecting the properties of a computer |
US6263362B1 (en) * | 1998-09-01 | 2001-07-17 | Bigfix, Inc. | Inspector for computed relevance messaging |
US7246150B1 (en) | 1998-09-01 | 2007-07-17 | Bigfix, Inc. | Advice provided for offering highly targeted advice without compromising individual privacy |
US6256664B1 (en) | 1998-09-01 | 2001-07-03 | Bigfix, Inc. | Method and apparatus for computed relevance messaging |
US8914507B2 (en) * | 1998-09-01 | 2014-12-16 | International Business Machines Corporation | Advice provided for offering highly targeted advice without compromising individual privacy |
USRE46153E1 (en) | 1998-09-11 | 2016-09-20 | Genesys Telecommunications Laboratories, Inc. | Method and apparatus enabling voice-based management of state and interaction of a remote knowledge worker in a contact center environment |
US6115709A (en) * | 1998-09-18 | 2000-09-05 | Tacit Knowledge Systems, Inc. | Method and system for constructing a knowledge profile of a user having unrestricted and restricted access portions according to respective levels of confidence of content of the portions |
US6490444B1 (en) * | 1998-10-06 | 2002-12-03 | Ameritech Corporation | Method and telecommunication system for indicating the receipt of a data message |
US6871220B1 (en) | 1998-10-28 | 2005-03-22 | Yodlee, Inc. | System and method for distributed storage and retrieval of personal information |
ATE273538T1 (en) | 1998-10-28 | 2004-08-15 | Verticalone Corp | APPARATUS AND METHOD FOR AUTOMATIC AGGREGATION AND SUPPLY OF ELECTRONIC PERSONAL INFORMATION OR DATA |
AU1122100A (en) * | 1998-10-30 | 2000-05-22 | Justsystem Pittsburgh Research Center, Inc. | Method for content-based filtering of messages by analyzing term characteristicswithin a message |
GB2343529B (en) * | 1998-11-07 | 2003-06-11 | Ibm | Filtering incoming e-mail |
US8069407B1 (en) | 1998-12-08 | 2011-11-29 | Yodlee.Com, Inc. | Method and apparatus for detecting changes in websites and reporting results to web developers for navigation template repair purposes |
US7200804B1 (en) * | 1998-12-08 | 2007-04-03 | Yodlee.Com, Inc. | Method and apparatus for providing automation to an internet navigation application |
US7672879B1 (en) | 1998-12-08 | 2010-03-02 | Yodlee.Com, Inc. | Interactive activity interface for managing personal data and performing transactions over a data packet network |
US7085997B1 (en) | 1998-12-08 | 2006-08-01 | Yodlee.Com | Network-based bookmark management and web-summary system |
US6546416B1 (en) * | 1998-12-09 | 2003-04-08 | Infoseek Corporation | Method and system for selectively blocking delivery of bulk electronic mail |
US6182081B1 (en) * | 1998-12-16 | 2001-01-30 | Bo Dietl | Method for performing in interactive review of data contents of a computer |
US7073129B1 (en) * | 1998-12-18 | 2006-07-04 | Tangis Corporation | Automated selection of appropriate information based on a computer user's context |
US6549957B1 (en) * | 1998-12-22 | 2003-04-15 | International Business Machines Corporation | Apparatus for preventing automatic generation of a chain reaction of messages if a prior extracted message is similar to current processed message |
US6654787B1 (en) | 1998-12-31 | 2003-11-25 | Brightmail, Incorporated | Method and apparatus for filtering e-mail |
US6330590B1 (en) * | 1999-01-05 | 2001-12-11 | William D. Cotten | Preventing delivery of unwanted bulk e-mail |
US6442589B1 (en) | 1999-01-14 | 2002-08-27 | Fujitsu Limited | Method and system for sorting and forwarding electronic messages and other data |
US6711154B1 (en) * | 1999-01-29 | 2004-03-23 | Microsoft Corporation | Apparatus and method for device independent messaging notification |
US7277919B1 (en) | 1999-03-19 | 2007-10-02 | Bigfix, Inc. | Relevance clause for computed relevance messaging |
US7039639B2 (en) | 1999-03-31 | 2006-05-02 | International Business Machines Corporation | Optimization of system performance based on communication relationship |
US6393423B1 (en) | 1999-04-08 | 2002-05-21 | James Francis Goedken | Apparatus and methods for electronic information exchange |
US6732149B1 (en) * | 1999-04-09 | 2004-05-04 | International Business Machines Corporation | System and method for hindering undesired transmission or receipt of electronic messages |
US6336117B1 (en) | 1999-04-30 | 2002-01-01 | International Business Machines Corporation | Content-indexing search system and method providing search results consistent with content filtering and blocking policies implemented in a blocking engine |
US6393464B1 (en) * | 1999-05-10 | 2002-05-21 | Unbound Communications, Inc. | Method for controlling the delivery of electronic mail messages |
AUPQ030299A0 (en) | 1999-05-12 | 1999-06-03 | Sharinga Networks Inc. | A message processing system |
CA2272739C (en) * | 1999-05-25 | 2003-10-07 | Suhayya Abu-Hakima | Apparatus and method for interpreting and intelligently managing electronic messages |
JP2000339236A (en) | 1999-05-27 | 2000-12-08 | Fujitsu Ltd | Mischievous mail preventing device, method therefor and recording medium |
US6718367B1 (en) * | 1999-06-01 | 2004-04-06 | General Interactive, Inc. | Filter for modeling system and method for handling and routing of text-based asynchronous communications |
US7752535B2 (en) | 1999-06-01 | 2010-07-06 | Yodlec.com, Inc. | Categorization of summarized information |
US6477565B1 (en) * | 1999-06-01 | 2002-11-05 | Yodlee.Com, Inc. | Method and apparatus for restructuring of personalized data for transmission from a data network to connected and portable network appliances |
US20040078423A1 (en) * | 2002-03-22 | 2004-04-22 | Ramakrishna Satyavolu | Method and apparatus for controlled establishment of a turnkey system providing a centralized data aggregation and summary capability to third party entities |
US6668281B1 (en) * | 1999-06-10 | 2003-12-23 | General Interactive, Inc. | Relationship management system and method using asynchronous electronic messaging |
US6546390B1 (en) | 1999-06-11 | 2003-04-08 | Abuzz Technologies, Inc. | Method and apparatus for evaluating relevancy of messages to users |
US6578025B1 (en) | 1999-06-11 | 2003-06-10 | Abuzz Technologies, Inc. | Method and apparatus for distributing information to users |
US6571238B1 (en) | 1999-06-11 | 2003-05-27 | Abuzz Technologies, Inc. | System for regulating flow of information to user by using time dependent function to adjust relevancy threshold |
US20040236721A1 (en) * | 2003-05-20 | 2004-11-25 | Jordan Pollack | Method and apparatus for distributing information to users |
US6539385B1 (en) | 1999-06-11 | 2003-03-25 | Abuzz Technologies, Inc. | Dual-use email system |
US6275470B1 (en) | 1999-06-18 | 2001-08-14 | Digital Island, Inc. | On-demand overlay routing for computer-based communication networks |
US6438583B1 (en) * | 1999-06-23 | 2002-08-20 | Re-Route Corporation | System and method for re-routing of e-mail messages |
AU5933700A (en) * | 1999-07-13 | 2001-01-30 | All Advantage. Com, Inc. | Method and system for classifying users of an electronic network |
US6741992B1 (en) * | 1999-07-29 | 2004-05-25 | Xtenit | Flexible rule-based communication system and method for controlling the flow of and access to information between computer users |
US6295559B1 (en) | 1999-08-26 | 2001-09-25 | International Business Machines Corporation | Rating hypermedia for objectionable content |
US7840639B1 (en) | 1999-09-21 | 2010-11-23 | G&H Nevada-Tek | Method and article of manufacture for an automatically executed application program associated with an electronic message |
US9092535B1 (en) | 1999-09-21 | 2015-07-28 | Google Inc. | E-mail embedded textual hyperlink object |
US6360221B1 (en) | 1999-09-21 | 2002-03-19 | Neostar, Inc. | Method and apparatus for the production, delivery, and receipt of enhanced e-mail |
WO2001024437A2 (en) | 1999-09-30 | 2001-04-05 | United States Postal Service | Systems and methods for authenticating an electronic message |
US7797543B1 (en) | 1999-09-30 | 2010-09-14 | United States Postal Service | Systems and methods for authenticating an electronic message |
US6510451B2 (en) | 1999-10-14 | 2003-01-21 | Yodlee.Com, Inc. | System for completing a multi-component task initiated by a client involving Web sites without requiring interaction from the client |
US8543901B1 (en) | 1999-11-01 | 2013-09-24 | Level 3 Communications, Llc | Verification of content stored in a network |
US6321267B1 (en) * | 1999-11-23 | 2001-11-20 | Escom Corporation | Method and apparatus for filtering junk email |
US7249175B1 (en) | 1999-11-23 | 2007-07-24 | Escom Corporation | Method and system for blocking e-mail having a nonexistent sender address |
US7929978B2 (en) | 1999-12-01 | 2011-04-19 | Genesys Telecommunications Laboratories, Inc. | Method and apparatus for providing enhanced communication capability for mobile devices on a virtual private network |
US6460050B1 (en) * | 1999-12-22 | 2002-10-01 | Mark Raymond Pace | Distributed content identification system |
DE60026472T2 (en) * | 1999-12-27 | 2006-11-02 | Hewlett-Packard Development Company, L.P., Houston | System and method for authenticating electronic messages sent to a network server |
US6508365B1 (en) * | 1999-12-28 | 2003-01-21 | Pitney Bowes Inc. | Method of removing mail from a mailstream using an incoming mail sorting apparatus |
US7072942B1 (en) * | 2000-02-04 | 2006-07-04 | Microsoft Corporation | Email filtering methods and systems |
US6460074B1 (en) | 2000-02-10 | 2002-10-01 | Martin E. Fishkin | Electronic mail system |
US6691156B1 (en) | 2000-03-10 | 2004-02-10 | International Business Machines Corporation | Method for restricting delivery of unsolicited E-mail |
US7624172B1 (en) | 2000-03-17 | 2009-11-24 | Aol Llc | State change alerts mechanism |
AU2001249230A1 (en) * | 2000-03-17 | 2001-10-03 | United States Postal Service | Methods and systems for establishing an electronic account for a customer |
US9246975B2 (en) | 2000-03-17 | 2016-01-26 | Facebook, Inc. | State change alerts mechanism |
US20040186996A1 (en) * | 2000-03-29 | 2004-09-23 | Gibbs Benjamin K. | Unique digital signature |
US6505245B1 (en) | 2000-04-13 | 2003-01-07 | Tecsys Development, Inc. | System and method for managing computing devices within a data communications network from a remotely located console |
AU2001263503A1 (en) * | 2000-05-16 | 2001-11-26 | America Online, Inc. | E-mail sender identification |
US7032023B1 (en) * | 2000-05-16 | 2006-04-18 | America Online, Inc. | Throttling electronic communications from one or more senders |
US7096220B1 (en) | 2000-05-24 | 2006-08-22 | Reachforce, Inc. | Web-based customer prospects harvester system |
US7082427B1 (en) | 2000-05-24 | 2006-07-25 | Reachforce, Inc. | Text indexing system to index, query the archive database document by keyword data representing the content of the documents and by contact data associated with the participant who generated the document |
US7120629B1 (en) | 2000-05-24 | 2006-10-10 | Reachforce, Inc. | Prospects harvester system for providing contact data about customers of product or service offered by business enterprise extracting text documents selected from newsgroups, discussion forums, mailing lists, querying such data to provide customers who confirm to business profile data |
US7003517B1 (en) * | 2000-05-24 | 2006-02-21 | Inetprofit, Inc. | Web-based system and method for archiving and searching participant-based internet text sources for customer lead data |
US20040073617A1 (en) | 2000-06-19 | 2004-04-15 | Milliken Walter Clark | Hash-based systems and methods for detecting and preventing transmission of unwanted e-mail |
WO2001099009A2 (en) * | 2000-06-20 | 2001-12-27 | United States Postal Service | Systems and methods for electronic message content identification |
US6981252B1 (en) | 2000-07-14 | 2005-12-27 | Symantec Corporation | Method and apparatus for automatically uninstalling software on a network |
US6779021B1 (en) | 2000-07-28 | 2004-08-17 | International Business Machines Corporation | Method and system for predicting and managing undesirable electronic mail |
JP2002049562A (en) * | 2000-08-03 | 2002-02-15 | Nec Access Technica Ltd | Electronic mail service system |
FR2812782B1 (en) * | 2000-08-03 | 2003-01-10 | France Telecom | SYSTEM FOR REGULATING ELECTRONIC MAIL AND INTERNET ACCESS FLOWS |
JP4548914B2 (en) * | 2000-08-24 | 2010-09-22 | 秀治 小川 | E-mail server device, e-mail service method, and information recording medium |
US7711790B1 (en) | 2000-08-24 | 2010-05-04 | Foundry Networks, Inc. | Securing an accessible computer system |
US7725587B1 (en) | 2000-08-24 | 2010-05-25 | Aol Llc | Deep packet scan hacker identification |
US6823331B1 (en) | 2000-08-28 | 2004-11-23 | Entrust Limited | Concept identification system and method for use in reducing and/or representing text content of an electronic document |
GB2366706B (en) | 2000-08-31 | 2004-11-03 | Content Technologies Ltd | Monitoring electronic mail messages digests |
US6952719B1 (en) * | 2000-09-26 | 2005-10-04 | Harris Scott C | Spam detector defeating system |
US6650890B1 (en) * | 2000-09-29 | 2003-11-18 | Postini, Inc. | Value-added electronic messaging services and transparent implementation thereof using intermediate server |
US7330850B1 (en) | 2000-10-04 | 2008-02-12 | Reachforce, Inc. | Text mining system for web-based business intelligence applied to web site server logs |
US7043531B1 (en) | 2000-10-04 | 2006-05-09 | Inetprofit, Inc. | Web-based customer lead generator system with pre-emptive profiling |
US6622909B1 (en) | 2000-10-24 | 2003-09-23 | Ncr Corporation | Mining data from communications filtering request |
US6778941B1 (en) | 2000-11-14 | 2004-08-17 | Qualia Computing, Inc. | Message and user attributes in a message filtering method and system |
US6781961B1 (en) | 2000-11-17 | 2004-08-24 | Emware, Inc. | Systems and methods for routing messages sent between computer systems |
US8539030B2 (en) * | 2000-11-22 | 2013-09-17 | Xerox Corporation | System and method for managing digests comprising electronic messages |
KR20020042060A (en) * | 2000-11-29 | 2002-06-05 | 한은석 | Method and system for confirming received email by confirming transmitted email between email transmitter-receiver |
US6938065B2 (en) * | 2000-12-12 | 2005-08-30 | Ericsson Inc. | System and method for controlling inclusion of email content |
US7174453B2 (en) * | 2000-12-29 | 2007-02-06 | America Online, Inc. | Message screening system |
US7054906B2 (en) * | 2000-12-29 | 2006-05-30 | Levosky Michael P | System and method for controlling and organizing Email |
US20020107925A1 (en) * | 2001-02-05 | 2002-08-08 | Robert Goldschneider | Method and system for e-mail management |
CN1316397C (en) * | 2001-02-12 | 2007-05-16 | Emc公司 | System and method of indexing unique electronic mail messages and uses for same |
US8219620B2 (en) * | 2001-02-20 | 2012-07-10 | Mcafee, Inc. | Unwanted e-mail filtering system including voting feedback |
WO2002069108A2 (en) * | 2001-02-26 | 2002-09-06 | Eprivacy Group, Inc. | System and method for controlling distribution of network communications |
US20020120581A1 (en) * | 2001-02-26 | 2002-08-29 | Schiavone Vincent J. | Reply based electronic mail transactions |
US7647411B1 (en) | 2001-02-26 | 2010-01-12 | Symantec Corporation | System and method for controlling distribution of network communications |
BR0208612A (en) * | 2001-03-22 | 2005-03-15 | Michael Chung | Method and systems for email, target and direct internet marketing, and email banner |
US7039700B2 (en) | 2001-04-04 | 2006-05-02 | Chatguard.Com | System and method for monitoring and analyzing communications |
US9767496B2 (en) | 2001-04-09 | 2017-09-19 | United States Postal Service | System and method for predelivery notification using mail image |
US8799183B2 (en) | 2001-04-09 | 2014-08-05 | United States Postal Service | System and method for predelivery notifcation using mail image |
AU2002256132A1 (en) * | 2001-04-09 | 2002-10-21 | United States Postal Service | System, method, and article of manufacture for filtering mail items based upon recipient preference |
US10346891B2 (en) * | 2001-04-09 | 2019-07-09 | United States Postal Service | System and method for predelivery notification using mail image |
US7779481B2 (en) * | 2001-04-12 | 2010-08-17 | United States Postal Service | Systems and methods for electronic postmarking of data including location data |
KR20020085445A (en) * | 2001-05-08 | 2002-11-16 | 유병찬 | Relationship management method using the communication network |
US7103599B2 (en) * | 2001-05-15 | 2006-09-05 | Verizon Laboratories Inc. | Parsing of nested internet electronic mail documents |
US20020198942A1 (en) * | 2001-06-20 | 2002-12-26 | Ryan Barbara Rae | Method and system for reducing unsolicited communications via multiple channels of communication |
US7043506B1 (en) | 2001-06-28 | 2006-05-09 | Microsoft Corporation | Utility-based archiving |
US7328250B2 (en) * | 2001-06-29 | 2008-02-05 | Nokia, Inc. | Apparatus and method for handling electronic mail |
GB0116771D0 (en) * | 2001-07-10 | 2001-08-29 | Ibm | System and method for tailoring of electronic messages |
US7647376B1 (en) | 2001-07-26 | 2010-01-12 | Mcafee, Inc. | SPAM report generation system and method |
US6769016B2 (en) | 2001-07-26 | 2004-07-27 | Networks Associates Technology, Inc. | Intelligent SPAM detection system using an updateable neural analysis engine |
US7016939B1 (en) | 2001-07-26 | 2006-03-21 | Mcafee, Inc. | Intelligent SPAM detection system using statistical analysis |
US20040205451A1 (en) * | 2001-08-13 | 2004-10-14 | International Business Machines Corporation | Method and system for identifying and distinguishing words contained within an electronic message in order to convey significance |
US20030046144A1 (en) * | 2001-08-28 | 2003-03-06 | International Business Machines Corporation | System and method for anonymous message forwarding and anonymous voting |
US8255235B2 (en) | 2001-09-07 | 2012-08-28 | United States Postal Service | Item tracking and anticipated delivery confirmation system method |
CN1575582A (en) * | 2001-09-28 | 2005-02-02 | 塞维斯通讯公司 | Configurable adaptive global traffic control and management |
US7860964B2 (en) * | 2001-09-28 | 2010-12-28 | Level 3 Communications, Llc | Policy-based content delivery network selection |
US7373644B2 (en) * | 2001-10-02 | 2008-05-13 | Level 3 Communications, Llc | Automated server replication |
JP3717829B2 (en) * | 2001-10-05 | 2005-11-16 | 日本デジタル株式会社 | Junk mail repelling system |
US20030079027A1 (en) * | 2001-10-18 | 2003-04-24 | Michael Slocombe | Content request routing and load balancing for content distribution networks |
US20080279222A1 (en) * | 2001-10-18 | 2008-11-13 | Level 3 Communications Llc | Distribution of traffic across a computer network |
EP3401794A1 (en) | 2002-01-08 | 2018-11-14 | Seven Networks, LLC | Connection architecture for a mobile network |
US20030149726A1 (en) * | 2002-02-05 | 2003-08-07 | At&T Corp. | Automating the reduction of unsolicited email in real time |
US9167036B2 (en) | 2002-02-14 | 2015-10-20 | Level 3 Communications, Llc | Managed object replication and delivery |
EP1476819B1 (en) * | 2002-02-19 | 2009-04-01 | Postini, Inc. | E-mail management services |
JP2003249962A (en) * | 2002-02-21 | 2003-09-05 | Fujitsu Ltd | Mail sorting device, mail server device, client device, mail distributing program, and client program |
US20030167321A1 (en) * | 2002-03-01 | 2003-09-04 | Schneider Automation Inc. | System and method for optimal setting of message acceptance filters |
US20060015942A1 (en) * | 2002-03-08 | 2006-01-19 | Ciphertrust, Inc. | Systems and methods for classification of messaging entities |
US8132250B2 (en) * | 2002-03-08 | 2012-03-06 | Mcafee, Inc. | Message profiling systems and methods |
US7124438B2 (en) * | 2002-03-08 | 2006-10-17 | Ciphertrust, Inc. | Systems and methods for anomaly detection in patterns of monitored communications |
US8561167B2 (en) | 2002-03-08 | 2013-10-15 | Mcafee, Inc. | Web reputation scoring |
US7458098B2 (en) | 2002-03-08 | 2008-11-25 | Secure Computing Corporation | Systems and methods for enhancing electronic communication security |
US7693947B2 (en) | 2002-03-08 | 2010-04-06 | Mcafee, Inc. | Systems and methods for graphically displaying messaging traffic |
US7694128B2 (en) | 2002-03-08 | 2010-04-06 | Mcafee, Inc. | Systems and methods for secure communication delivery |
US6941467B2 (en) * | 2002-03-08 | 2005-09-06 | Ciphertrust, Inc. | Systems and methods for adaptive message interrogation through multiple queues |
US7870203B2 (en) | 2002-03-08 | 2011-01-11 | Mcafee, Inc. | Methods and systems for exposing messaging reputation to an end user |
US8578480B2 (en) | 2002-03-08 | 2013-11-05 | Mcafee, Inc. | Systems and methods for identifying potentially malicious messages |
US7903549B2 (en) * | 2002-03-08 | 2011-03-08 | Secure Computing Corporation | Content-based policy compliance systems and methods |
US7096498B2 (en) * | 2002-03-08 | 2006-08-22 | Cipher Trust, Inc. | Systems and methods for message threat management |
US7596600B2 (en) * | 2002-03-28 | 2009-09-29 | Quine Douglas B | System for selective delivery of electronic communications |
AUPS193202A0 (en) * | 2002-04-23 | 2002-05-30 | Pickup, Robert Barkley Mr | A method and system for authorising electronic mail |
US20030216982A1 (en) * | 2002-05-17 | 2003-11-20 | Tyler Close | Messaging gateway for incentivizing collaboration |
US7139801B2 (en) * | 2002-06-14 | 2006-11-21 | Mindshare Design, Inc. | Systems and methods for monitoring events associated with transmitted electronic mail messages |
US7516182B2 (en) * | 2002-06-18 | 2009-04-07 | Aol Llc | Practical techniques for reducing unsolicited electronic messages by identifying sender's addresses |
US7310660B1 (en) | 2002-06-25 | 2007-12-18 | Engate Technology Corporation | Method for removing unsolicited e-mail messages |
US8046832B2 (en) * | 2002-06-26 | 2011-10-25 | Microsoft Corporation | Spam detector with challenges |
US8219709B2 (en) * | 2002-07-05 | 2012-07-10 | Carolyn J Hughes | Method for internet name sharing |
US7490128B1 (en) | 2002-09-09 | 2009-02-10 | Engate Technology Corporation | Unsolicited message rejecting communications processor |
US7673058B1 (en) | 2002-09-09 | 2010-03-02 | Engate Technology Corporation | Unsolicited message intercepting communications processor |
US7716351B1 (en) | 2002-09-09 | 2010-05-11 | Engate Technology Corporation | Unsolicited message diverting communications processor |
US7010565B2 (en) * | 2002-09-30 | 2006-03-07 | Sampson Scott E | Communication management using a token action log |
US20060168089A1 (en) * | 2002-09-30 | 2006-07-27 | Sampson Scott E | Controlling incoming communication by issuing tokens |
US6804687B2 (en) * | 2002-09-30 | 2004-10-12 | Scott E. Sampson | File system management with user-definable functional attributes stored in a token action log |
US8051172B2 (en) * | 2002-09-30 | 2011-11-01 | Sampson Scott E | Methods for managing the exchange of communication tokens |
US20040073688A1 (en) * | 2002-09-30 | 2004-04-15 | Sampson Scott E. | Electronic payment validation using Transaction Authorization Tokens |
JP4007893B2 (en) | 2002-10-03 | 2007-11-14 | 株式会社エヌ・ティ・ティ・ドコモ | Server device, program, and recording medium |
US20040068543A1 (en) * | 2002-10-03 | 2004-04-08 | Ralph Seifert | Method and apparatus for processing e-mail |
US7469280B2 (en) * | 2002-11-04 | 2008-12-23 | Sun Microsystems, Inc. | Computer implemented system and method for predictive management of electronic messages |
US20040167991A1 (en) * | 2002-11-08 | 2004-08-26 | Ups, Inc. | Method for providing gated network access |
WO2004046867A2 (en) | 2002-11-18 | 2004-06-03 | America Online, Inc. | People lists |
US8122137B2 (en) | 2002-11-18 | 2012-02-21 | Aol Inc. | Dynamic location of a subordinate user |
US8701014B1 (en) | 2002-11-18 | 2014-04-15 | Facebook, Inc. | Account linking |
US7899862B2 (en) | 2002-11-18 | 2011-03-01 | Aol Inc. | Dynamic identification of other users to an online user |
US8005919B2 (en) | 2002-11-18 | 2011-08-23 | Aol Inc. | Host-based intelligent results related to a character stream |
US7428580B2 (en) | 2003-11-26 | 2008-09-23 | Aol Llc | Electronic message forwarding |
US8965964B1 (en) | 2002-11-18 | 2015-02-24 | Facebook, Inc. | Managing forwarded electronic messages |
US7640306B2 (en) | 2002-11-18 | 2009-12-29 | Aol Llc | Reconfiguring an electronic message to effect an enhanced notification |
US7590696B1 (en) | 2002-11-18 | 2009-09-15 | Aol Llc | Enhanced buddy list using mobile device identifiers |
US6732157B1 (en) * | 2002-12-13 | 2004-05-04 | Networks Associates Technology, Inc. | Comprehensive anti-spam system, method, and computer program product for filtering unwanted e-mail messages |
US7624110B2 (en) | 2002-12-13 | 2009-11-24 | Symantec Corporation | Method, system, and computer program product for security within a global computer network |
US7640336B1 (en) | 2002-12-30 | 2009-12-29 | Aol Llc | Supervising user interaction with online services |
US20040139042A1 (en) * | 2002-12-31 | 2004-07-15 | Schirmer Andrew L. | System and method for improving data analysis through data grouping |
US7917468B2 (en) | 2005-08-01 | 2011-03-29 | Seven Networks, Inc. | Linking of personal information management data |
US8468126B2 (en) | 2005-08-01 | 2013-06-18 | Seven Networks, Inc. | Publishing data in an information community |
US7853563B2 (en) | 2005-08-01 | 2010-12-14 | Seven Networks, Inc. | Universal data aggregation |
US7620691B1 (en) | 2003-02-10 | 2009-11-17 | Aol Llc | Filtering electronic messages while permitting delivery of solicited electronics messages |
US7603472B2 (en) | 2003-02-19 | 2009-10-13 | Google Inc. | Zero-minute virus and spam detection |
US20060265459A1 (en) * | 2003-02-19 | 2006-11-23 | Postini, Inc. | Systems and methods for managing the transmission of synchronous electronic messages |
US7958187B2 (en) * | 2003-02-19 | 2011-06-07 | Google Inc. | Systems and methods for managing directory harvest attacks via electronic messages |
US7249162B2 (en) * | 2003-02-25 | 2007-07-24 | Microsoft Corporation | Adaptive junk message filtering system |
US7543053B2 (en) * | 2003-03-03 | 2009-06-02 | Microsoft Corporation | Intelligent quarantining for spam prevention |
US7219148B2 (en) * | 2003-03-03 | 2007-05-15 | Microsoft Corporation | Feedback loop for spam prevention |
US20050091320A1 (en) * | 2003-10-09 | 2005-04-28 | Kirsch Steven T. | Method and system for categorizing and processing e-mails |
US7366761B2 (en) * | 2003-10-09 | 2008-04-29 | Abaca Technology Corporation | Method for creating a whitelist for processing e-mails |
US7206814B2 (en) * | 2003-10-09 | 2007-04-17 | Propel Software Corporation | Method and system for categorizing and processing e-mails |
US20040177120A1 (en) * | 2003-03-07 | 2004-09-09 | Kirsch Steven T. | Method for filtering e-mail messages |
US20050080857A1 (en) * | 2003-10-09 | 2005-04-14 | Kirsch Steven T. | Method and system for categorizing and processing e-mails |
US20050091319A1 (en) * | 2003-10-09 | 2005-04-28 | Kirsch Steven T. | Database for receiving, storing and compiling information about email messages |
EP1604293A2 (en) * | 2003-03-07 | 2005-12-14 | Propel Software Corporation | Method for filtering e-mail messages |
DE10310151A1 (en) * | 2003-03-07 | 2004-09-16 | Linde Ag | Method for operating a fuel system for an LPG engine |
US7529754B2 (en) | 2003-03-14 | 2009-05-05 | Websense, Inc. | System and method of monitoring and controlling application files |
US7185015B2 (en) | 2003-03-14 | 2007-02-27 | Websense, Inc. | System and method of monitoring and controlling application files |
US7603417B2 (en) | 2003-03-26 | 2009-10-13 | Aol Llc | Identifying and using identities deemed to be known to a user |
US7373519B1 (en) | 2003-04-09 | 2008-05-13 | Symantec Corporation | Distinguishing legitimate modifications from malicious modifications during executable computer file modification analysis |
US7290033B1 (en) | 2003-04-18 | 2007-10-30 | America Online, Inc. | Sorting electronic messages using attributes of the sender address |
US20040221012A1 (en) * | 2003-04-30 | 2004-11-04 | Hewlett-Packard Development Company, L.P. | E-mail forward filter |
US7483947B2 (en) * | 2003-05-02 | 2009-01-27 | Microsoft Corporation | Message rendering for identification of content features |
US7590695B2 (en) * | 2003-05-09 | 2009-09-15 | Aol Llc | Managing electronic messages |
US20050108340A1 (en) * | 2003-05-15 | 2005-05-19 | Matt Gleeson | Method and apparatus for filtering email spam based on similarity measures |
WO2004107137A2 (en) * | 2003-05-24 | 2004-12-09 | Safe E Messaging, Llc | Method and code for authenticating electronic messages |
US7657599B2 (en) * | 2003-05-29 | 2010-02-02 | Mindshare Design, Inc. | Systems and methods for automatically updating electronic mail access lists |
US7272853B2 (en) * | 2003-06-04 | 2007-09-18 | Microsoft Corporation | Origination/destination features and lists for spam prevention |
US8145710B2 (en) * | 2003-06-18 | 2012-03-27 | Symantec Corporation | System and method for filtering spam messages utilizing URL filtering module |
US7711779B2 (en) * | 2003-06-20 | 2010-05-04 | Microsoft Corporation | Prevention of outgoing spam |
US7519668B2 (en) * | 2003-06-20 | 2009-04-14 | Microsoft Corporation | Obfuscation of spam filter |
US8533270B2 (en) * | 2003-06-23 | 2013-09-10 | Microsoft Corporation | Advanced spam detection techniques |
US7562119B2 (en) * | 2003-07-15 | 2009-07-14 | Mindshare Design, Inc. | Systems and methods for automatically updating electronic mail access lists |
US7590693B1 (en) * | 2003-07-17 | 2009-09-15 | Avaya Inc. | Method and apparatus for restriction of message distribution for security |
US7653693B2 (en) | 2003-09-05 | 2010-01-26 | Aol Llc | Method and system for capturing instant messages |
US7627635B1 (en) | 2003-07-28 | 2009-12-01 | Aol Llc | Managing self-addressed electronic messages |
US7184160B2 (en) * | 2003-08-08 | 2007-02-27 | Venali, Inc. | Spam fax filter |
US8321512B2 (en) * | 2003-08-22 | 2012-11-27 | Geobytes, Inc. | Method and software product for identifying unsolicited emails |
US20050060643A1 (en) * | 2003-08-25 | 2005-03-17 | Miavia, Inc. | Document similarity detection and classification system |
US20050055404A1 (en) * | 2003-09-04 | 2005-03-10 | Information Processing Corporation | E-mail server registry and method |
US9338026B2 (en) | 2003-09-22 | 2016-05-10 | Axway Inc. | Delay technique in e-mail filtering system |
US8271588B1 (en) | 2003-09-24 | 2012-09-18 | Symantec Corporation | System and method for filtering fraudulent email messages |
US7130819B2 (en) * | 2003-09-30 | 2006-10-31 | Yahoo! Inc. | Method and computer readable medium for search scoring |
US7536442B2 (en) * | 2003-09-30 | 2009-05-19 | International Business Machines Corporation | Method, system, and storage medium for providing autonomic identification of an important message |
DE10394323T5 (en) * | 2003-10-17 | 2006-11-23 | Aspect Communications Corp., San Jose | Method and system for providing expert support with a customer interaction system |
US7395314B2 (en) * | 2003-10-28 | 2008-07-01 | Mindshare Design, Inc. | Systems and methods for governing the performance of high volume electronic mail delivery |
US7844589B2 (en) * | 2003-11-18 | 2010-11-30 | Yahoo! Inc. | Method and apparatus for performing a search |
US7660857B2 (en) * | 2003-11-21 | 2010-02-09 | Mindshare Design, Inc. | Systems and methods for automatically updating electronic mail access lists |
US20050125667A1 (en) * | 2003-12-09 | 2005-06-09 | Tim Sullivan | Systems and methods for authorizing delivery of incoming messages |
US20050160258A1 (en) * | 2003-12-11 | 2005-07-21 | Bioobservation Systems Limited | Detecting objectionable content in displayed images |
US7882360B2 (en) | 2003-12-19 | 2011-02-01 | Aol Inc. | Community messaging lists for authorization to deliver electronic messages |
US7730137B1 (en) | 2003-12-22 | 2010-06-01 | Aol Inc. | Restricting the volume of outbound electronic messages originated by a single entity |
US7224778B2 (en) * | 2003-12-30 | 2007-05-29 | Aol Llc. | Method and apparatus for managing subscription-type messages |
US7653816B2 (en) | 2003-12-30 | 2010-01-26 | First Information Systems, Llc | E-mail certification service |
US20050193130A1 (en) * | 2004-01-22 | 2005-09-01 | Mblx Llc | Methods and systems for confirmation of availability of messaging account to user |
US20050188031A1 (en) * | 2004-01-30 | 2005-08-25 | Zandt Thomas V. | Methods and apparatuses for increasing the timeliness and accuracy with which electronic mail massages are communicated |
US8224902B1 (en) | 2004-02-04 | 2012-07-17 | At&T Intellectual Property Ii, L.P. | Method and apparatus for selective email processing |
US7469292B2 (en) * | 2004-02-11 | 2008-12-23 | Aol Llc | Managing electronic messages using contact information |
US8214438B2 (en) | 2004-03-01 | 2012-07-03 | Microsoft Corporation | (More) advanced spam detection features |
US20050198159A1 (en) * | 2004-03-08 | 2005-09-08 | Kirsch Steven T. | Method and system for categorizing and processing e-mails based upon information in the message header and SMTP session |
US20050204006A1 (en) * | 2004-03-12 | 2005-09-15 | Purcell Sean E. | Message junk rating interface |
ATE381744T1 (en) * | 2004-03-20 | 2008-01-15 | Boewe Bell & Howell Gmbh | OBJECT FILTER FOR ORGANIZING THE DISTRIBUTION OF MAIL |
US7647321B2 (en) * | 2004-04-26 | 2010-01-12 | Google Inc. | System and method for filtering electronic messages using business heuristics |
US7941490B1 (en) | 2004-05-11 | 2011-05-10 | Symantec Corporation | Method and apparatus for detecting spam in email messages and email attachments |
CN101288060B (en) * | 2004-05-25 | 2012-11-07 | 波斯蒂尼公司 | Electronic message source reputation information system |
US7664819B2 (en) * | 2004-06-29 | 2010-02-16 | Microsoft Corporation | Incremental anti-spam lookup and update service |
CA2473157A1 (en) * | 2004-07-13 | 2006-01-13 | John D. Swain | A method to establish legitimacy of communications |
US7904517B2 (en) * | 2004-08-09 | 2011-03-08 | Microsoft Corporation | Challenge response systems |
US7660865B2 (en) | 2004-08-12 | 2010-02-09 | Microsoft Corporation | Spam filtering with probabilistic secure hashes |
FR2868899A1 (en) * | 2004-10-15 | 2005-10-14 | France Telecom | Message broadcasting process for e.g. Internet network, involves successively transmitting message to recipients of broadcasting list in order specified by list upon receiving negative response message |
WO2006045102A2 (en) | 2004-10-20 | 2006-04-27 | Seven Networks, Inc. | Method and apparatus for intercepting events in a communication system |
US8010082B2 (en) | 2004-10-20 | 2011-08-30 | Seven Networks, Inc. | Flexible billing architecture |
US8635690B2 (en) | 2004-11-05 | 2014-01-21 | Mcafee, Inc. | Reputation based message processing |
US7706781B2 (en) | 2004-11-22 | 2010-04-27 | Seven Networks International Oy | Data security in a mobile e-mail service |
FI117152B (en) | 2004-12-03 | 2006-06-30 | Seven Networks Internat Oy | E-mail service provisioning method for mobile terminal, involves using domain part and further parameters to generate new parameter set in list of setting parameter sets, if provisioning of e-mail service is successful |
US8396927B2 (en) * | 2004-12-21 | 2013-03-12 | Alcatel Lucent | Detection of unwanted messages (spam) |
DE102005010690B4 (en) * | 2005-03-09 | 2007-04-12 | Knorr-Bremse Systeme für Schienenfahrzeuge GmbH | Oil-injected compressor with temperature switch |
US7877703B1 (en) | 2005-03-14 | 2011-01-25 | Seven Networks, Inc. | Intelligent rendering of information in a limited display environment |
US7650383B2 (en) * | 2005-03-15 | 2010-01-19 | Aol Llc | Electronic message system with federation of trusted senders |
US7647381B2 (en) * | 2005-04-04 | 2010-01-12 | Aol Llc | Federated challenge credit system |
US8438633B1 (en) | 2005-04-21 | 2013-05-07 | Seven Networks, Inc. | Flexible real-time inbox access |
US7796742B1 (en) | 2005-04-21 | 2010-09-14 | Seven Networks, Inc. | Systems and methods for simplified provisioning |
US8135778B1 (en) | 2005-04-27 | 2012-03-13 | Symantec Corporation | Method and apparatus for certifying mass emailings |
US20060253597A1 (en) * | 2005-05-05 | 2006-11-09 | Mujica Technologies Inc. | E-mail system |
US20060271629A1 (en) * | 2005-05-26 | 2006-11-30 | Macdowell Alexander D | Distributed Challenge and Response Recognition System |
US7937480B2 (en) * | 2005-06-02 | 2011-05-03 | Mcafee, Inc. | Aggregation of reputation data |
US8010609B2 (en) * | 2005-06-20 | 2011-08-30 | Symantec Corporation | Method and apparatus for maintaining reputation lists of IP addresses to detect email spam |
US7739337B1 (en) | 2005-06-20 | 2010-06-15 | Symantec Corporation | Method and apparatus for grouping spam email messages |
WO2006136660A1 (en) | 2005-06-21 | 2006-12-28 | Seven Networks International Oy | Maintaining an ip connection in a mobile network |
GB0512744D0 (en) * | 2005-06-22 | 2005-07-27 | Blackspider Technologies | Method and system for filtering electronic messages |
US7930353B2 (en) * | 2005-07-29 | 2011-04-19 | Microsoft Corporation | Trees of classifiers for detecting email spam |
US8069166B2 (en) | 2005-08-01 | 2011-11-29 | Seven Networks, Inc. | Managing user-to-user contact with inferred presence information |
US20070088793A1 (en) * | 2005-10-17 | 2007-04-19 | Landsman Richard A | Filter for instant messaging |
US8065370B2 (en) | 2005-11-03 | 2011-11-22 | Microsoft Corporation | Proofs to filter spam |
US9008075B2 (en) | 2005-12-22 | 2015-04-14 | Genesys Telecommunications Laboratories, Inc. | System and methods for improving interaction routing performance |
US20070180034A1 (en) * | 2006-02-02 | 2007-08-02 | Ditroia John | Method and system for filtering communication |
US8601160B1 (en) | 2006-02-09 | 2013-12-03 | Mcafee, Inc. | System, method and computer program product for gathering information relating to electronic content utilizing a DNS server |
US7769395B2 (en) | 2006-06-20 | 2010-08-03 | Seven Networks, Inc. | Location-based operations and messaging |
US9152949B2 (en) * | 2006-05-17 | 2015-10-06 | International Business Machines Corporation | Methods and apparatus for identifying spam email |
US8842818B2 (en) * | 2006-06-30 | 2014-09-23 | Avaya Inc. | IP telephony architecture including information storage and retrieval system to track fluency |
US7606752B2 (en) | 2006-09-07 | 2009-10-20 | Yodlee Inc. | Host exchange in bill paying services |
US8180835B1 (en) | 2006-10-14 | 2012-05-15 | Engate Technology Corporation | System and method for protecting mail servers from mail flood attacks |
US20080104181A1 (en) * | 2006-10-26 | 2008-05-01 | Tal Golan | Electronic mail processing system |
US8527592B2 (en) | 2006-10-31 | 2013-09-03 | Watchguard Technologies, Inc. | Reputation-based method and system for determining a likelihood that a message is undesired |
US8135780B2 (en) * | 2006-12-01 | 2012-03-13 | Microsoft Corporation | Email safety determination |
US8224905B2 (en) | 2006-12-06 | 2012-07-17 | Microsoft Corporation | Spam filtration utilizing sender activity data |
CA2574439A1 (en) * | 2007-01-08 | 2008-07-08 | Mark F. Van Coeverden De Groot | Extended methods for establishing legitimacy of communications: precomputed demonstrations of legitimacy and other approaches |
GB2458094A (en) * | 2007-01-09 | 2009-09-09 | Surfcontrol On Demand Ltd | URL interception and categorization in firewalls |
US8179798B2 (en) * | 2007-01-24 | 2012-05-15 | Mcafee, Inc. | Reputation based connection throttling |
US7779156B2 (en) * | 2007-01-24 | 2010-08-17 | Mcafee, Inc. | Reputation based load balancing |
US8763114B2 (en) | 2007-01-24 | 2014-06-24 | Mcafee, Inc. | Detecting image spam |
US8214497B2 (en) | 2007-01-24 | 2012-07-03 | Mcafee, Inc. | Multi-dimensional reputation scoring |
US7949716B2 (en) | 2007-01-24 | 2011-05-24 | Mcafee, Inc. | Correlation and analysis of entity attributes |
US7973644B2 (en) | 2007-01-30 | 2011-07-05 | Round Rock Research, Llc | Systems and methods for RFID tag arbitration where RFID tags generate multiple random numbers for different arbitration sessions |
US7761523B2 (en) * | 2007-02-09 | 2010-07-20 | Research In Motion Limited | Schedulable e-mail filters |
TW200839561A (en) * | 2007-03-22 | 2008-10-01 | Wistron Corp | Method of irregular password configuration and verification |
GB0709527D0 (en) | 2007-05-18 | 2007-06-27 | Surfcontrol Plc | Electronic messaging system, message processing apparatus and message processing method |
US8134452B2 (en) * | 2007-05-30 | 2012-03-13 | Round Rock Research, Llc | Methods and systems of receiving data payload of RFID tags |
US8805425B2 (en) | 2007-06-01 | 2014-08-12 | Seven Networks, Inc. | Integrated messaging |
US8693494B2 (en) | 2007-06-01 | 2014-04-08 | Seven Networks, Inc. | Polling |
US20080313285A1 (en) * | 2007-06-14 | 2008-12-18 | Microsoft Corporation | Post transit spam filtering |
US10671600B1 (en) | 2007-07-24 | 2020-06-02 | Avaya Inc. | Communications-enabled dynamic social network routing utilizing presence |
US8488764B1 (en) | 2007-07-24 | 2013-07-16 | Avaya Inc. | Conference call selectable configuration in which participants can be configured to join at different time (order), use presence information to configure/initiate the conference call |
US8428367B2 (en) * | 2007-10-26 | 2013-04-23 | International Business Machines Corporation | System and method for electronic document classification |
US8185930B2 (en) * | 2007-11-06 | 2012-05-22 | Mcafee, Inc. | Adjusting filter or classification control settings |
US8045458B2 (en) * | 2007-11-08 | 2011-10-25 | Mcafee, Inc. | Prioritizing network traffic |
US8364181B2 (en) | 2007-12-10 | 2013-01-29 | Seven Networks, Inc. | Electronic-mail filtering for mobile devices |
US9002828B2 (en) | 2007-12-13 | 2015-04-07 | Seven Networks, Inc. | Predictive content delivery |
US8793305B2 (en) * | 2007-12-13 | 2014-07-29 | Seven Networks, Inc. | Content delivery to a mobile device from a content service |
US8346953B1 (en) | 2007-12-18 | 2013-01-01 | AOL, Inc. | Methods and systems for restricting electronic content access based on guardian control decisions |
US8107921B2 (en) | 2008-01-11 | 2012-01-31 | Seven Networks, Inc. | Mobile virtual network operator |
US8160975B2 (en) * | 2008-01-25 | 2012-04-17 | Mcafee, Inc. | Granular support vector machine with random granularity |
US8862657B2 (en) | 2008-01-25 | 2014-10-14 | Seven Networks, Inc. | Policy based content service |
US20090193338A1 (en) | 2008-01-28 | 2009-07-30 | Trevor Fiatal | Reducing network and battery consumption during content delivery and playback |
US9762692B2 (en) | 2008-04-04 | 2017-09-12 | Level 3 Communications, Llc | Handling long-tail content in a content delivery network (CDN) |
US10924573B2 (en) | 2008-04-04 | 2021-02-16 | Level 3 Communications, Llc | Handling long-tail content in a content delivery network (CDN) |
US8930538B2 (en) | 2008-04-04 | 2015-01-06 | Level 3 Communications, Llc | Handling long-tail content in a content delivery network (CDN) |
US8589503B2 (en) | 2008-04-04 | 2013-11-19 | Mcafee, Inc. | Prioritizing network traffic |
US8261334B2 (en) | 2008-04-25 | 2012-09-04 | Yodlee Inc. | System for performing web authentication of a user by proxy |
US7970814B2 (en) * | 2008-05-20 | 2011-06-28 | Raytheon Company | Method and apparatus for providing a synchronous interface for an asynchronous service |
EP2304924A1 (en) | 2008-05-20 | 2011-04-06 | Raytheon Company | System and method for maintaining stateful information |
EP2281387A4 (en) * | 2008-05-20 | 2013-03-20 | Raytheon Co | System and method for collaborative messaging and data distribution |
EP2301208A1 (en) * | 2008-05-20 | 2011-03-30 | Raytheon Company | System and method for dynamic contact lists |
US8112487B2 (en) * | 2008-05-20 | 2012-02-07 | Raytheon Company | System and method for message filtering |
US8787947B2 (en) | 2008-06-18 | 2014-07-22 | Seven Networks, Inc. | Application discovery on mobile devices |
US8078158B2 (en) | 2008-06-26 | 2011-12-13 | Seven Networks, Inc. | Provisioning applications for a mobile device |
US8909759B2 (en) | 2008-10-10 | 2014-12-09 | Seven Networks, Inc. | Bandwidth measurement |
US8555359B2 (en) | 2009-02-26 | 2013-10-08 | Yodlee, Inc. | System and methods for automatically accessing a web site on behalf of a client |
US9177264B2 (en) | 2009-03-06 | 2015-11-03 | Chiaramail, Corp. | Managing message categories in a network |
US10169599B2 (en) * | 2009-08-26 | 2019-01-01 | International Business Machines Corporation | Data access control with flexible data disclosure |
US9224007B2 (en) | 2009-09-15 | 2015-12-29 | International Business Machines Corporation | Search engine with privacy protection |
US8862674B2 (en) * | 2009-11-30 | 2014-10-14 | At&T Intellectual Property I, L.P. | Method and apparatus for managing an electronic messaging system |
US9600134B2 (en) | 2009-12-29 | 2017-03-21 | International Business Machines Corporation | Selecting portions of computer-accessible documents for post-selection processing |
WO2011126889A2 (en) | 2010-03-30 | 2011-10-13 | Seven Networks, Inc. | 3d mobile user interface with configurable workspace management |
US8621638B2 (en) | 2010-05-14 | 2013-12-31 | Mcafee, Inc. | Systems and methods for classification of messaging entities |
US8495003B2 (en) | 2010-06-08 | 2013-07-23 | NHaK, Inc. | System and method for scoring stream data |
US8838783B2 (en) | 2010-07-26 | 2014-09-16 | Seven Networks, Inc. | Distributed caching for resource and mobile network traffic management |
US9077630B2 (en) | 2010-07-26 | 2015-07-07 | Seven Networks, Inc. | Distributed implementation of dynamic wireless traffic policy |
US9043433B2 (en) | 2010-07-26 | 2015-05-26 | Seven Networks, Inc. | Mobile network traffic coordination across multiple applications |
GB2500333B (en) | 2010-07-26 | 2014-10-08 | Seven Networks Inc | Mobile application traffic optimization |
US8326985B2 (en) | 2010-11-01 | 2012-12-04 | Seven Networks, Inc. | Distributed management of keep-alive message signaling for mobile network resource conservation and optimization |
WO2012060995A2 (en) | 2010-11-01 | 2012-05-10 | Michael Luna | Distributed caching in a wireless network of content delivered for a mobile application over a long-held request |
US8484314B2 (en) | 2010-11-01 | 2013-07-09 | Seven Networks, Inc. | Distributed caching in a wireless network of content delivered for a mobile application over a long-held request |
US8166164B1 (en) | 2010-11-01 | 2012-04-24 | Seven Networks, Inc. | Application and network-based long poll request detection and cacheability assessment therefor |
US9330196B2 (en) | 2010-11-01 | 2016-05-03 | Seven Networks, Llc | Wireless traffic management system cache optimization using http headers |
US9060032B2 (en) | 2010-11-01 | 2015-06-16 | Seven Networks, Inc. | Selective data compression by a distributed traffic management system to reduce mobile data traffic and signaling traffic |
US8843153B2 (en) | 2010-11-01 | 2014-09-23 | Seven Networks, Inc. | Mobile traffic categorization and policy for network use optimization while preserving user experience |
WO2012061437A1 (en) | 2010-11-01 | 2012-05-10 | Michael Luna | Cache defeat detection and caching of content addressed by identifiers intended to defeat cache |
GB2499534B (en) | 2010-11-01 | 2018-09-19 | Seven Networks Llc | Caching adapted for mobile application behavior and network conditions |
GB2500327B (en) | 2010-11-22 | 2019-11-06 | Seven Networks Llc | Optimization of resource polling intervals to satisfy mobile device requests |
GB2495463B (en) | 2010-11-22 | 2013-10-09 | Seven Networks Inc | Aligning data transfer to optimize connections established for transmission over a wireless network |
GB2501416B (en) | 2011-01-07 | 2018-03-21 | Seven Networks Llc | System and method for reduction of mobile network traffic used for domain name system (DNS) queries |
WO2012145533A2 (en) | 2011-04-19 | 2012-10-26 | Seven Networks, Inc. | Shared resource and virtual resource management in a networked environment |
WO2012149434A2 (en) | 2011-04-27 | 2012-11-01 | Seven Networks, Inc. | Detecting and preserving state for satisfying application requests in a distributed proxy and cache system |
GB2504037B (en) | 2011-04-27 | 2014-12-24 | Seven Networks Inc | Mobile device which offloads requests made by a mobile application to a remote entity for conservation of mobile device and network resources |
WO2013015994A1 (en) | 2011-07-27 | 2013-01-31 | Seven Networks, Inc. | Monitoring mobile application activities for malicious traffic on a mobile device |
US8868753B2 (en) | 2011-12-06 | 2014-10-21 | Seven Networks, Inc. | System of redundantly clustered machines to provide failover mechanisms for mobile traffic management and network resource conservation |
US8934414B2 (en) | 2011-12-06 | 2015-01-13 | Seven Networks, Inc. | Cellular or WiFi mobile traffic optimization based on public or private network destination |
WO2013086447A1 (en) | 2011-12-07 | 2013-06-13 | Seven Networks, Inc. | Radio-awareness of mobile device for sending server-side control signals using a wireless network optimized transport protocol |
US9009250B2 (en) | 2011-12-07 | 2015-04-14 | Seven Networks, Inc. | Flexible and dynamic integration schemas of a traffic management system with various network operators for network traffic alleviation |
US9832095B2 (en) | 2011-12-14 | 2017-11-28 | Seven Networks, Llc | Operation modes for mobile traffic optimization and concurrent management of optimized and non-optimized traffic |
US8861354B2 (en) | 2011-12-14 | 2014-10-14 | Seven Networks, Inc. | Hierarchies and categories for management and deployment of policies for distributed wireless traffic optimization |
EP2792188B1 (en) | 2011-12-14 | 2019-03-20 | Seven Networks, LLC | Mobile network reporting and usage analytics system and method using aggregation of data in a distributed traffic optimization system |
GB2499306B (en) | 2012-01-05 | 2014-10-22 | Seven Networks Inc | Managing user interaction with an application on a mobile device |
US9195853B2 (en) | 2012-01-15 | 2015-11-24 | International Business Machines Corporation | Automated document redaction |
WO2013116856A1 (en) | 2012-02-02 | 2013-08-08 | Seven Networks, Inc. | Dynamic categorization of applications for network access in a mobile network |
US9326189B2 (en) | 2012-02-03 | 2016-04-26 | Seven Networks, Llc | User as an end point for profiling and optimizing the delivery of content and data in a wireless network |
US8812695B2 (en) | 2012-04-09 | 2014-08-19 | Seven Networks, Inc. | Method and system for management of a virtual network connection without heartbeat messages |
US10263899B2 (en) | 2012-04-10 | 2019-04-16 | Seven Networks, Llc | Enhanced customer service for mobile carriers using real-time and historical mobile application and traffic or optimization data associated with mobile devices in a mobile network |
WO2014011216A1 (en) | 2012-07-13 | 2014-01-16 | Seven Networks, Inc. | Dynamic bandwidth adjustment for browsing or streaming activity in a wireless network based on prediction of user behavior when interacting with mobile applications |
US9161258B2 (en) | 2012-10-24 | 2015-10-13 | Seven Networks, Llc | Optimized and selective management of policy deployment to mobile clients in a congested network to prevent further aggravation of network congestion |
US9892278B2 (en) | 2012-11-14 | 2018-02-13 | International Business Machines Corporation | Focused personal identifying information redaction |
US9241259B2 (en) | 2012-11-30 | 2016-01-19 | Websense, Inc. | Method and apparatus for managing the transfer of sensitive information to mobile devices |
US9307493B2 (en) | 2012-12-20 | 2016-04-05 | Seven Networks, Llc | Systems and methods for application management of mobile device radio state promotion and demotion |
US9241314B2 (en) | 2013-01-23 | 2016-01-19 | Seven Networks, Llc | Mobile device with application or context aware fast dormancy |
US8874761B2 (en) | 2013-01-25 | 2014-10-28 | Seven Networks, Inc. | Signaling optimization in a wireless network for traffic utilizing proprietary and non-proprietary protocols |
US8750123B1 (en) | 2013-03-11 | 2014-06-10 | Seven Networks, Inc. | Mobile device equipped with mobile network congestion recognition to make intelligent decisions regarding connecting to an operator network |
US9065765B2 (en) | 2013-07-22 | 2015-06-23 | Seven Networks, Inc. | Proxy server associated with a mobile carrier for enhancing mobile traffic management in a mobile network |
US9928465B2 (en) | 2014-05-20 | 2018-03-27 | Oath Inc. | Machine learning and validation of account names, addresses, and/or identifiers |
CN110213152B (en) * | 2018-05-02 | 2021-09-14 | 腾讯科技(深圳)有限公司 | Method, device, server and storage medium for identifying junk mails |
Family Cites Families (2)
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US5093918A (en) * | 1988-12-22 | 1992-03-03 | International Business Machines Corporation | System using independent attribute lists to show status of shared mail object among respective users |
GB8918553D0 (en) * | 1989-08-15 | 1989-09-27 | Digital Equipment Int | Message control system |
-
1994
- 1994-11-30 US US08/346,715 patent/US5619648A/en not_active Expired - Lifetime
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1995
- 1995-10-05 CA CA002159973A patent/CA2159973C/en not_active Expired - Lifetime
- 1995-11-21 EP EP95308342A patent/EP0720333B1/en not_active Expired - Lifetime
- 1995-11-21 DE DE69535395T patent/DE69535395T2/en not_active Expired - Lifetime
- 1995-11-29 JP JP7332561A patent/JP3066300B2/en not_active Expired - Lifetime
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DE69535395D1 (en) | 2007-04-05 |
EP0720333A3 (en) | 2005-08-03 |
EP0720333B1 (en) | 2007-02-21 |
JPH08263404A (en) | 1996-10-11 |
DE69535395T2 (en) | 2007-10-31 |
EP0720333A2 (en) | 1996-07-03 |
US5619648A (en) | 1997-04-08 |
JP3066300B2 (en) | 2000-07-17 |
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