US20120046068A1 - Automatically performing user actions based on detected context-to-user-action correlations - Google Patents
Automatically performing user actions based on detected context-to-user-action correlations Download PDFInfo
- Publication number
- US20120046068A1 US20120046068A1 US12/764,143 US76414310A US2012046068A1 US 20120046068 A1 US20120046068 A1 US 20120046068A1 US 76414310 A US76414310 A US 76414310A US 2012046068 A1 US2012046068 A1 US 2012046068A1
- Authority
- US
- United States
- Prior art keywords
- user
- context
- action
- user device
- cac
- 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.)
- Abandoned
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
-
- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0204—Market segmentation
-
- 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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- 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
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/02—Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks
- H04W8/08—Mobility data transfer
- H04W8/16—Mobility data transfer selectively restricting mobility data tracking
Definitions
- the present disclosure relates to automatically performing user actions at a user device based on a context of the user device.
- a user may set his mobile phone to a silent mode when in an important meeting or in a movie theater and set his mobile phone to ring at a maximum volume level when in a noisy environment such as a shopping mall.
- performing such controls can become tedious.
- forgetting to perform such controls can oftentimes lead to embarrassing situations such as a ringing mobile telephone while watching a movie at a movie theater.
- a system and method are provided for automatically performing user actions on a device based on a context of the user device.
- user actions taken by a user of a user device and corresponding contexts of the user device at times at which the user actions were taken are monitored to detect correlations between contexts of the user device and user actions taken by the user, which are referred to herein as context-to-user-action correlations.
- Each context-to-user-action correlation defines a context of the user device and a user action historically taken by the user of the user device for when the device is in that context.
- a current context of the user device is obtained and compared to the stored context-to-user-action correlations to identify a matching context-to-user-action correlation.
- the user device then automatically performs the user action that is correlated to the current context as defined by the matching context-to-user-action correlation.
- the user may be prompted for approval to perform the user action before performing the user action.
- FIG. 1 illustrates a mobile device including a Context to user Action Correlation (CAC) function according to one embodiment of the present disclosure
- FIG. 2 is a flow chart illustrating the operation of the CAC function of FIG. 1 according to one embodiment of the present disclosure
- FIGS. 3A through 3C provide a flow chart illustrating the operation of the CAC function of FIG. 1 in more detail according to one embodiment of the present disclosure.
- FIG. 4 is a block diagram of the mobile device of FIG. 1 according to one embodiment of the present disclosure.
- FIG. 1 illustrates a mobile device 10 including a Context to user Action Correlation (CAC) function 12 according to one embodiment of the present disclosure.
- CAC Context to user Action Correlation
- the mobile device 10 is a mobile device such as, for example, a mobile smart phone (e.g., an Apple® iPhone), a portable media player (e.g., an Apple® iPod Touch® device), a laptop or notebook computer, a tablet computer (e.g., Apple® iPad), or the like.
- the mobile device 10 includes the CAC function 12 , one or more context sensors 14 , and a CAC record repository 16 .
- the CAC function 12 is preferably implemented in software, but may be implemented as a combination of hardware and software. In operation, the CAC function 12 monitors user actions taken by a user of the mobile device 10 and contexts of the mobile device 10 obtained from the context sensors 14 at times at which the user actions were taken by the user.
- the context of the mobile device 10 includes a list of device identifiers (IDs) of a number of mobile devices 18 located proximate to the mobile device 10 , a list of user IDs for users of the mobile devices 18 located proximate to the mobile device 10 , a list of users in a social network of the user of the mobile device 10 that are proximate to the mobile device 10 , a list of users in a contact list maintained by the mobile device 10 that are proximate to the mobile device 10 , or a combination thereof.
- the other mobile devices 18 preferably have similar internal structures as the mobile device 10 . Different reference numbers are used for the mobile device 10 and the other mobile devices 18 to enable the mobile devices 10 and 18 to be differentiated in the discussion herein.
- the context of the mobile device 10 may include a location of the mobile device 10 where the location of the mobile device 10 may be expressed as geospatial coordinates (e.g., latitude and longitude coordinates), a physical address (e.g., a street address), a predefined location designation (e.g., “work” or “home”), Wi-Fi hotspot ID, or the like.
- geospatial coordinates e.g., latitude and longitude coordinates
- a physical address e.g., a street address
- predefined location designation e.g., “work” or “home”
- Wi-Fi hotspot ID e.g., Wi-Fi hotspot ID, or the like.
- the context of the mobile device 10 may include data defining one or more ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density as estimated by, for example, a number of proximate mobile devices 18 detected in the local wireless coverage area of the mobile device 10 , crowd composition, geographic information system labels or metadata, or the like.
- the context of the mobile device 10 may include data from an accelerometer of the mobile device 10 , which may indicate whether the user of the mobile device 10 is walking, jogging, driving, sitting, or the like.
- the context of the mobile device 10 may include a number of the mobile devices 10 having unknown users.
- Unknown users are users that are not known to the user of the mobile device 10 in a social network, contact list, or the like.
- the number of unknown users proximate to the mobile device 10 may be indicative of being located in a public venue such as a sporting arena for a sporting event, concert, or the like.
- the context of the mobile device 10 may include data obtained from an electronic calendar maintained for the user of the mobile device 10 such as a status identifier for the user (e.g., “Meeting with Bob”) or the like.
- the user actions monitored by the CAC function 12 are generally user actions taken by the user of the mobile device 10 to interact with the mobile device 10 .
- the user actions monitored by the CAC function 12 may be any user action taken by the user to interact with the mobile device 10 .
- the CAC function 12 may only monitor for a defined set of user actions taken by the user to interact with the mobile device 10 (e.g., monitor only volume control actions).
- some exemplary user actions that may be monitored by the CAC function 12 include, but are not limited to, volume control actions, turning off the mobile device 10 , turning off a local wireless communication interface of the mobile device 10 , activating a software application, closing a software application, changing a particular setting on the mobile device 10 , or the like.
- the CAC function 12 may monitor user actions with respect to the mobile device 10 in general.
- the CAC function 12 may monitor user actions only with respect to one or more defined software applications running on the mobile device 10 .
- the CAC function 12 may be incorporated into a particular software application and only monitor only those user actions made by the user with respect to that software application.
- the CAC function 12 is enabled to detect correlations between contexts of the mobile device 10 and user actions taken by the user of the mobile device 10 .
- Each detected correlation between a context and a user action taken by the user of the mobile device 10 defines a context of the mobile device 10 and a user action that has historically been taken by the user when the mobile device 10 is in that context.
- the CAC function 12 may then use the stored context-to-user-action correlations to automatically perform user actions in response to detecting the correlated contexts.
- the context sensors 14 may be implemented in hardware, software, or a combination thereof.
- the context sensors 14 are software and/or hardware components that are enabled to obtain data forming the context of the mobile device 10 .
- the context sensors 14 preferably include a local wireless communication interface such as, for example, a Bluetooth® communication interface or a communication interface operating according to one of the suite of IEEE 802.11x standards (i.e., a Wi-Fi communication interface).
- the CAC function 12 is enabled to obtain a list of device IDs of mobile devices 18 that are located proximate to the mobile device 10 , user IDs of users of the mobile devices 18 that are located proximate to the mobile device 10 , or a combination thereof.
- the devices 18 that are proximate to the mobile device 10 are mobile devices 18 that are within a wireless coverage area of the mobile device 10 and/or mobile devices 18 for which the mobile device 10 is in their wireless coverage areas.
- the mobile device 10 may obtain the device IDs of the mobile devices 18 and/or user IDs of the users of the mobile devices 18 by passively monitoring wireless communications to or from the mobile devices 18 , by actively querying the mobile devices 18 for their device IDs or the user IDs of their users, or both.
- the context sensors 14 may also include a software application that interacts with a social networking service (e.g., the Facebook® social networking service) to identify other users in the social network of the user of the mobile device 10 that are currently located proximate to the mobile device 10 .
- a social networking service is also to include an Instant Messaging service or the like.
- the mobile device 10 may query the social networking service via a network connection (e.g., an Internet connection) with the device IDs of the mobile devices 18 or the user IDs of the users of the mobile devices 18 .
- the social networking service stores device IDs and/or user IDs for at least some of the users of the social networking service.
- the social networking service in response to receiving the query, identifies users of the social networking service that correspond to the IDs included in the query, if any, and determines which of the identified users are in the social network of the user of the mobile device 10 .
- the social networking service then returns information identifying the users in the social network of the user of the mobile device 10 that have IDs matching those of the mobile devices 18 or users of the mobile devices 18 that are proximate to the mobile device 10 .
- the mobile device 10 may query an intermediate device or service between the mobile device 10 and the social networking service.
- the social networking service tracks locations of users of the social networking service.
- CAC function 12 of the mobile device 10 may query the social networking service for members of the social network of the user of the mobile device 10 that are currently located proximate to the current location of the mobile device 10 .
- the social networking service determines which members of the social network of the user of the mobile device 10 are proximate to the current location of the mobile device 10 and returns information identifying those members to the CAC function 12 at the mobile device 10 .
- members of the social network of the user are proximate to the current location of the mobile device 10 if, for example, they are within a defined distance from the current location of the mobile device 10 , at the same street address as the mobile device 10 , or the like.
- a contact list of may be maintained and stored at the mobile device 10 that include a number of contacts of the user.
- the contact list may also include device IDs of mobile devices associated with at least some of the contacts.
- the CAC function 12 may then use the device IDs of the mobile devices 18 and the device IDSs in the contact list to identify other users in the contact list of the user that are currently proximate to the mobile device 10 .
- the context sensors 14 may also include a location determination function that operates to sense or otherwise obtain the location of the mobile device 10 .
- the location determination function may be, but is not limited to, a Global Positioning System (GPS) receiver.
- the context sensors 14 may also include one or more context sensors 14 for detecting or otherwise obtaining ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density, or the like.
- the context sensors 14 may detect the ambient conditions directly or obtain the ambient conditions from a remote device or service (e.g., an Internet based weather service).
- the one or more context sensors 14 may include an accelerometer for detecting user or device movement.
- the context sensors 14 may include a software component for obtaining relevant contextual data from an electronic calendar maintained for the user of the mobile device 10 , where the electronic calendar may be stored locally at the mobile device 10 or remotely by, for example, an Internet based service.
- the CAC record repository 16 stores a number of CAC records for potential context-to-user-action correlations, which are referred to herein as potential CAC records, and a number of CAC records for actual context-to-user-action correlations, which are referred to herein as actual CAC records.
- Each CAC record whether potential or actual, defines a user action and a context of the mobile device 10 .
- the CAC record may include a counter that counts the number of times the defined user action has been detected when the mobile device 10 is in the defined context, timestamps defining times at which the defined user action has been detected when the mobile device 10 is in the defined context, or both.
- the CAC record may also include a flag, or indicator, that indicates whether the CAC record is for an actual context-to-user-action correlation or a potential context or user action correlation.
- FIG. 2 is a flow chart illustrating the operation of the CAC function 12 of FIG. 1 according to one embodiment of the present disclosure.
- the CAC function 12 detects correlations between contexts of the mobile device 10 and user actions taken by the user of the mobile device 10 (step 100 ). More specifically, the CAC function 12 monitors the user actions taken by the user at the mobile device 10 and the context of the mobile device 10 at the times the user actions were taken. Over time, via results of the monitoring, the CAC function 12 detects correlations between contexts of the mobile device 10 and user actions taken by the user of the mobile device 10 . In general, a context-to-user-action correlation is detected when the user of the mobile device 10 has historically performed a particular user action when the mobile device 10 is in a particular context.
- One or more system-defined or user-configurable rules may be used by the CAC function 12 to determine when a context-to-user-action correlation has been detected.
- the CAC function 12 may detect a context-to-user-action correlation when the user of the mobile device 10 has performed a particular user action at the mobile device 10 when the mobile device 10 is in a particular context, or in a number of matching contexts, at least a defined minimum number of times (e.g., three times).
- the CAC function 12 may detect this as a context-to-user-action correlation.
- matching contexts are contexts that match exactly or match at least to a predefined threshold degree.
- the CAC function 12 may detect a context-to-user-action correlation when the user of the mobile device 10 has performed a particular user action at the mobile device 10 when the mobile device 10 is in a particular context, or in a group of matching contexts, at least a defined minimum number of times (e.g., three times) within a defined amount of time (e.g., one month).
- a defined minimum number of times e.g., three times
- a defined amount of time e.g., one month
- the CAC function 12 may enable the user of the mobile device 10 to manually define one or more context-to-user-action correlations. These user-defined context-to-user-action correlations may then be used by the CAC function 12 to automatically perform the defined user actions in response to detecting the corresponding contexts in the manner described below.
- the CAC function 102 then obtains a current context of the mobile device 10 (step 102 ).
- the current context of the mobile device 10 includes a list of device IDs of the mobile devices 18 currently located proximate to the mobile device 10 , a list of user IDs for users of the mobile devices 18 currently located proximate to the mobile device 10 , a list of users in a social network of the user of the mobile device 10 that are currently proximate to the mobile device 10 , a list of users in a contact list maintained by the mobile device 10 that are proximate to the mobile device 10 , or a combination thereof.
- the current context of the mobile device 10 may include a current location of the mobile device 10 where the current location of the mobile device 10 may be expressed as geospatial coordinates (e.g., latitude and longitude coordinates), a physical address (e.g., a street address), a predefined location designation (e.g., “work” or “home”), Wi-Fi hotspot ID, or the like. Still further, the current context of the mobile device 10 may include data defining one or more current ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density, or the like. Further, the context of the mobile device 10 may include data from an accelerometer that is indicative of user or device movement. Still further, the current context of the mobile device 10 may include data obtained from an electronic calendar maintained for the user of the mobile device 10 such as an event or meeting that the user is currently scheduled to be attending.
- geospatial coordinates e.g., latitude and longitude coordinates
- a physical address e.g
- the CAC function 12 then automatically performs a user action that is correlated to the current context, if any (step 104 ).
- the CAC function 12 automatically performs the user action by first prompting the user of the mobile device 10 for approval to perform the user action and then performing the user action upon receiving approval from the user.
- the CAC function 12 automatically performs the user action without user interaction from the user of the mobile device 10 (e.g., without first prompting the user for approval).
- the CAC function 12 may, after automatically performing the user action, provide an alert to the user indicating that the user action has been taken and why the user action has been taken (e.g., the context that triggered the user action).
- contexts may be named by the user as part of the context-to-user-action creation process.
- FIGS. 3A through 3C provide a flow chart illustrating the operation of the CAC function 12 of FIG. 1 in more detail according to one embodiment of the present disclosure.
- the CAC function 12 monitors for a user action (step 200 ).
- the user actions monitored for by the CAC function 12 are generally user actions taken by the user of the mobile device 10 to interact with the mobile device 10 .
- the user actions monitored by the CAC function 12 may be any user action taken by the user to interact with the mobile device 10 .
- the CAC function 12 may only monitor for a defined set of user actions taken by the user to interact with the mobile device 10 (e.g., monitor only volume control actions). Further, the CAC function 12 may monitor user actions with respect to the mobile device 10 in general.
- the CAC function 12 may monitor user actions only with respect to one or more defined software applications running on the mobile device 10 . The CAC function 12 then determines whether a user action has been detected (step 202 ). Note that while illustrated separately, steps 200 and 202 may be implemented as a single step. If a user action has been detected, the CAC function 12 obtains the current context of the mobile device 10 (step 204 ).
- a matching CAC record is either a potential CAC record or an actual CAC record in the CAC record repository 16 of the mobile device 10 having a defined context that matches the current context of the mobile device 10 and a defined user action that matches the detected user action from steps 200 and 202 .
- contexts match if they match exactly or at least to a predefined threshold degree.
- One or more system-defined rules and/or one or more user-configurable rules may be used to determine whether the defined context of a CAC record matches the current context of the mobile device 10 .
- the one or more rules may state that, for example, the defined context of the CAC record matches the current context of the mobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the CAC record exactly matches the corresponding contextual component of the current context of the mobile device 10 .
- each contextual component e.g., list of device IDs, location, etc.
- the one or more rules may state that the defined context of the CAC record matches the current context of the mobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the CAC record matches the corresponding contextual component of the current context of the mobile device 10 to at least a defined threshold degree (e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context).
- each contextual component e.g., list of device IDs, location, etc.
- a defined threshold degree e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context.
- the one or more rules may state that the defined context of the CAC record matches the current context of the mobile device 10 if some contextual components (e.g., list of device IDs) of the defined context for the CAC record match the corresponding contextual components of the current context of the mobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the CAC record exactly match the corresponding contextual components of the current context of the mobile device 10 .
- some contextual components e.g., list of device IDs
- the defined context for the CAC record match the corresponding contextual components of the current context of the mobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the CAC record exactly
- the CAC function 12 If there is no matching CAC record (referring to step 206 ), the CAC function 12 creates a potential CAC record for the current context of the mobile device 10 and the detected user action and stores the potential CAC record in the CAC record repository 16 (step 208 ), and then the process returns to step 200 and is repeated. If there is a matching CAC record, the CAC function 12 determines whether the matching CAC record is an actual CAC record (step 210 ). If the matching CAC record is not an actual CAC record, the matching CAC record is a potential CAC record. As such, the CAC function 12 then updates the matching potential CAC record to reflect detection of the user action (step 212 ).
- the matching potential CAC record includes a counter for the number of times the user action has been detected in the defined context. As such, the CAC function 12 may then increase the counter by a value of one (1).
- the matching potential CAC record includes a timestamp for each occurrence of the user action for the defined context. As such, the CAC function 12 may add a timestamp to the matching potential CAC record defining the current time to indicate that the user action was detected with respect to the defined context at the current time.
- the defined context of the matching potential CAC record may be updated based on the current context. This is particularly the case where the current context matches the defined context for the matching potential CAC record less than exactly.
- any device IDs and/or user IDs in the current context that are not included in the defined context for the matching potential CAC record may be added to the defined context for the matching potential CAC record. Note that, before adding the user IDs to the defined context, this condition may be required to occur a threshold number of times within a defined period of time.
- the CAC function 12 determines whether a pattern has been detected for the matching potential CAC record (step 214 ).
- a pattern is detected when the matching potential CAC record indicates that the user of the mobile device 10 has historically performed the defined user action when the mobile device 10 is in the defined context.
- One or more system-defined or user-configurable rules may be used by the CAC function 12 to determine when a pattern has been detected.
- the CAC function 12 may detect a pattern when the number of occurrences for the user action defined by the matching potential CAC record for the context defined by the matching potential CAC record, as indicated by the counter stored in the matching potential CAC record, is greater than a defined threshold number of occurrences (e.g., three times).
- the defined threshold number of occurrences may be user-defined or system-defined.
- the CAC function 12 may track the number of times that the user must typically be prompted regarding a potential CAC record before the user approves promoting the potential CAC record to an actual CAC record (see below) and then set the defined threshold number of occurrences to that number.
- the defined threshold number of occurrences may be set to three.
- the CAC function 12 may detect a pattern when a frequency of occurrence for the user action defined by the matching potential CAC record for the context defined by the matching potential CAC record is greater than a defined threshold frequency of occurrence.
- the frequency of occurrence may be defined from timestamps stored in the matching potential CAC record for occurrences of the defined user action when in the defined context.
- the defined threshold frequency of occurrence may be three times over the last month. Note that the aforementioned examples are illustrative and are not intended to limit the scope of the present disclosure. Other types of rules may be used.
- the process returns to step 200 and is repeated. If a pattern is detected, in this embodiment, the CAC function 12 prompts the user of the mobile device 10 for approval to promote the matching potential CAC record to an actual CAC record (step 216 ). In other words, the CAC function 12 prompts the user of the mobile device 10 for approval to promote the matching potential CAC to an actual CAC. The CAC function 12 then determines whether approval has been received from the user of the mobile device 10 (step 218 ). If not, the process returns to step 200 and is repeated. If approval is received from the user, the CAC function 12 promotes the matching potential CAC record to an actual CAC record (step 220 ). In other words, the matching potential CAC is promoted to an actual CAC.
- the matching potential CAC record includes a flag indicating that the matching potential CAC record is a potential CAC record.
- the matching potential CAC record may be promoted to an actual CAC record by setting the flag such that the flag indicates that the matching potential CAC record is now an actual CAC record.
- promoting the matching potential CAC record to an actual CAC record may include prompting the user for a name for the actual CAC record or more specifically a name for the context defined by the actual CAC record, which may be used, for example, when displaying alerts. At this point, the process returns to step 200 and is repeated.
- steps 216 and 218 are optional.
- the user is not prompted for approval. Rather, the matching, potential CAC record is automatically promoted to an actual CAC record without interaction from the user of the mobile device 10 . Further note that whether the user is prompted for approval may be a user configurable setting.
- the CAC function 12 updates the actual CAC record to reflect the detection of the user action (step 222 ).
- the defined context for the actual CAC record may be updated based on the current context in a manner to that described above. The process then returns to step 200 and is repeated.
- the CAC function 12 obtains the current context of the mobile device 10 (step 224 ) and determines whether there are one or more matching actual CAC records stored in the CAC record repository 16 (step 226 ).
- the matching actual CAC records are actual CAC records that define contexts that match the current context of the mobile device 10 . Again, contexts match if they match exactly or at least a predefined threshold degree.
- One or more system-defined rules and/or one or more user-configurable rules may be used to determine whether the defined context of an actual CAC record matches the current context of the mobile device 10 .
- the one or more rules may state that, for example, the defined context of the actual CAC record matches the current context of the mobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the actual CAC record exactly matches the corresponding contextual component of the current context of the mobile device 10 .
- each contextual component e.g., list of device IDs, location, etc.
- the one or more rules may state that the defined context of the actual CAC record matches the current context of the mobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the actual CAC record matches the corresponding contextual component of the current context of the mobile device 10 to at least a defined threshold degree (e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context).
- each contextual component e.g., list of device IDs, location, etc.
- a defined threshold degree e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context.
- the one or more rules may state that the defined context of the actual CAC record matches the current context of the mobile device 10 if some contextual components (e.g., list of device IDs) of the defined context for the actual CAC record match the corresponding contextual components of the current context of the mobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the actual CAC record exactly match the corresponding contextual components of the current context of the mobile device 10 .
- some contextual components e.g., list of device IDs
- the defined context for the actual CAC record match the corresponding contextual components of the current context of the mobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the actual CAC record exactly match
- the process returns to step 200 and is repeated. If there are one or more matching actual CAC records, the CAC function 12 gets the next matching actual CAC record and the user action defined by the matching actual CAC record (steps 228 and 230 ). Note that there may be multiple matching actual CAC records where, for example, the user of the mobile device 10 has historically taken multiple user actions when in the same context.
- the CAC function 12 then prompts the user of the mobile device 10 for approval to take the user action defined by the matching actual CAC record (step 232 ).
- the CAC function 12 determines whether approval has been received from the user (step 234 ). If approval is not received, the process proceeds to step 238 .
- the CAC function 12 may record that fact that approval was not received in association with or as part of the CAC record. This information could be used by the CAC function 12 to identify and avoid future false alarms. If approval is received, the CAC function 12 performs the user action defined by the matching actual CAC record (step 236 ). Note that steps 232 and 234 are optional. In another embodiment, the user is not prompted for approval. Rather, the user action defined by the matching actual CAC record is automatically performed without first prompting for user approval.
- approval whether or not approval is requested from the user before performing the user action may be determined by the CAC function 12 on a case-by-case basis based on user configuration, user-defined or system-defined rules, whether the user has given approval for taking the user action in response to detecting the corresponding context in the past, or whether the user has given approval for taking similar user actions in the past. For example, if the user has always or almost always allowed a user action for turning off a ringer of the mobile device 10 when in a “movie theater” context, the CAC function 12 may automatically perform that user action in response to detecting the “movie theater” context without first prompting the user for approval. In contrast, if the user has not consistently turned off the ringer of the mobile device 10 when in a “meeting” context, then the CAC function 12 may prompt the user for approval before performing that user action in response to detecting the “meeting” context.
- the CAC function 12 may monitor user actions for a short time (e.g., 5-10 seconds) after automatically performing the user action to see if the user reverses the user action. Whether the user reverses the automatically performed user action may then be stored in the CAC record and used by the CAC function 12 to, for example, determine whether to prompt the user for approval before performing the user action in response to detecting the corresponding context in the future.
- a short time e.g., 5-10 seconds
- the CAC function 12 determines whether there are more matching actual CAC records to process (step 238 ). If so, the process returns to step 228 and is repeated. Once all of the matching actual CAC records have been processed, the process returns to step 200 and is repeated. Note that numerous variations to the process of FIGS. 3A through 3C will be apparent to one of ordinary skill in the art upon reading this disclosure and are considered within the scope of the present disclosure. For example, steps 228 - 238 may be modified such that the user is prompted for approval for the user actions defined by all of the matching actual CAC records at once.
- the user may be presented with a list of user actions, where the user is enabled to approve any number of the user actions from the list as he or she may desire. Also, along with each user action in the list, the user may be presented with the corresponding context and the contextual components that triggered the inclusion of the user action in the list. The user may then be enabled to edit this list to modify the CAC records for future occurrences.
- FIG. 4 is a block diagram of the mobile device 10 according to one embodiment of the present disclosure.
- the mobile device 10 includes a controller 20 connected to memory 22 , one or more secondary storage devices 24 , one or more communication interfaces 26 , one or more user interface components 28 , and one or more context sensors 14 by a bus 30 or similar mechanism.
- the controller 20 is a microprocessor, digital ASIC, FPGA, or the like.
- the controller 20 is a microprocessor, and the CAC function 12 is implemented in software and stored in the memory 22 for execution by the controller 20 .
- one or more of the context sensors 14 may be implemented in software and stored in the memory 22 for execution by the controller 20 .
- the one or more secondary storage devices 24 are digital storage devices such as, for example, one or more hard disk drives.
- the CAC record repository 16 is implemented in the one or more secondary storage devices 24 .
- the one or more communication interfaces 26 preferably include a local wireless communication interface such as, but not limited to, a Bluetooth® interface or an IEEE 802.11x interface.
- the one or more communication interfaces 26 may include a cellular telecommunications interface (e.g., GSM, LTE, W-CDMA, WiMAX, or the like).
- a cellular telecommunications interface e.g., GSM, LTE, W-CDMA, WiMAX, or the like.
- an IEEE 802.11x interface or a cellular telecommunications interface may be utilized to connect to a remote service such as, for example, a social networking service, an Internet based weather service, or the like.
- the local wireless communication interface may be used as, or as part of, one of the context sensors 14 .
- the one or more user interface components 28 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof.
- one or more of the user interface components 28 may be used as, or as part of, one or more of the context sensors 14 .
- a microphone user interface component may be used to sense an ambient sound level.
- the mobile device 10 may include one or more additional context sensors 14 such as, for example, a GPS receiver, or an ambient condition sensor (e.g., a temperature sensor).
Abstract
Description
- This application claims the benefit of provisional patent application Ser. No. 61/173,625, filed Apr. 29, 2009, the disclosure of which is hereby incorporated herein by reference in its entirety.
- The present disclosure relates to automatically performing user actions at a user device based on a context of the user device.
- Users often control their mobile devices differently in different contexts. For instance, a user may set his mobile phone to a silent mode when in an important meeting or in a movie theater and set his mobile phone to ring at a maximum volume level when in a noisy environment such as a shopping mall. However, performing such controls can become tedious. Further, forgetting to perform such controls can oftentimes lead to embarrassing situations such as a ringing mobile telephone while watching a movie at a movie theater. As such, there is a need for a system and method of performing user actions on a mobile phone based on context in a manner that is automatic or that requires minimal user input.
- A system and method are provided for automatically performing user actions on a device based on a context of the user device. In one embodiment, user actions taken by a user of a user device and corresponding contexts of the user device at times at which the user actions were taken are monitored to detect correlations between contexts of the user device and user actions taken by the user, which are referred to herein as context-to-user-action correlations. Each context-to-user-action correlation defines a context of the user device and a user action historically taken by the user of the user device for when the device is in that context. Subsequently, a current context of the user device is obtained and compared to the stored context-to-user-action correlations to identify a matching context-to-user-action correlation. The user device then automatically performs the user action that is correlated to the current context as defined by the matching context-to-user-action correlation. Optionally, the user may be prompted for approval to perform the user action before performing the user action.
- Those skilled in the art will appreciate the scope of the present invention and realize additional aspects thereof after reading the following detailed description of the preferred embodiments in association with the accompanying drawing figures.
- The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the invention, and together with the description serve to explain the principles of the invention.
-
FIG. 1 illustrates a mobile device including a Context to user Action Correlation (CAC) function according to one embodiment of the present disclosure; -
FIG. 2 is a flow chart illustrating the operation of the CAC function ofFIG. 1 according to one embodiment of the present disclosure; -
FIGS. 3A through 3C provide a flow chart illustrating the operation of the CAC function ofFIG. 1 in more detail according to one embodiment of the present disclosure; and -
FIG. 4 is a block diagram of the mobile device ofFIG. 1 according to one embodiment of the present disclosure. - The embodiments set forth below represent the necessary information to enable those skilled in the art to practice the invention and illustrate the best mode of practicing the invention. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the invention and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure and the accompanying claims.
-
FIG. 1 illustrates amobile device 10 including a Context to user Action Correlation (CAC)function 12 according to one embodiment of the present disclosure. Note that while the discussion herein focuses on themobile device 10, theCAC function 12 may additionally or alternatively be implemented on other types of user devices (i.e., non-mobile user devices such as personal computers, set-top boxes, audio systems, or the like). Themobile device 10 is a mobile device such as, for example, a mobile smart phone (e.g., an Apple® iPhone), a portable media player (e.g., an Apple® iPod Touch® device), a laptop or notebook computer, a tablet computer (e.g., Apple® iPad), or the like. - As illustrated, the
mobile device 10 includes theCAC function 12, one ormore context sensors 14, and aCAC record repository 16. TheCAC function 12 is preferably implemented in software, but may be implemented as a combination of hardware and software. In operation, theCAC function 12 monitors user actions taken by a user of themobile device 10 and contexts of themobile device 10 obtained from thecontext sensors 14 at times at which the user actions were taken by the user. In the preferred embodiment, the context of themobile device 10 includes a list of device identifiers (IDs) of a number ofmobile devices 18 located proximate to themobile device 10, a list of user IDs for users of themobile devices 18 located proximate to themobile device 10, a list of users in a social network of the user of themobile device 10 that are proximate to themobile device 10, a list of users in a contact list maintained by themobile device 10 that are proximate to themobile device 10, or a combination thereof. Note that the othermobile devices 18 preferably have similar internal structures as themobile device 10. Different reference numbers are used for themobile device 10 and the othermobile devices 18 to enable themobile devices - In addition, the context of the
mobile device 10 may include a location of themobile device 10 where the location of themobile device 10 may be expressed as geospatial coordinates (e.g., latitude and longitude coordinates), a physical address (e.g., a street address), a predefined location designation (e.g., “work” or “home”), Wi-Fi hotspot ID, or the like. Still further, the context of themobile device 10 may include data defining one or more ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density as estimated by, for example, a number of proximatemobile devices 18 detected in the local wireless coverage area of themobile device 10, crowd composition, geographic information system labels or metadata, or the like. Still further, the context of themobile device 10 may include data from an accelerometer of themobile device 10, which may indicate whether the user of themobile device 10 is walking, jogging, driving, sitting, or the like. Still further, the context of themobile device 10 may include a number of themobile devices 10 having unknown users. Unknown users are users that are not known to the user of themobile device 10 in a social network, contact list, or the like. The number of unknown users proximate to themobile device 10 may be indicative of being located in a public venue such as a sporting arena for a sporting event, concert, or the like. Still further, the context of themobile device 10 may include data obtained from an electronic calendar maintained for the user of themobile device 10 such as a status identifier for the user (e.g., “Meeting with Bob”) or the like. - The user actions monitored by the
CAC function 12 are generally user actions taken by the user of themobile device 10 to interact with themobile device 10. The user actions monitored by theCAC function 12 may be any user action taken by the user to interact with themobile device 10. Alternatively, theCAC function 12 may only monitor for a defined set of user actions taken by the user to interact with the mobile device 10 (e.g., monitor only volume control actions). While the types of user actions may depend on the particular implementation, some exemplary user actions that may be monitored by theCAC function 12 include, but are not limited to, volume control actions, turning off themobile device 10, turning off a local wireless communication interface of themobile device 10, activating a software application, closing a software application, changing a particular setting on themobile device 10, or the like. Further, theCAC function 12 may monitor user actions with respect to themobile device 10 in general. Alternatively, theCAC function 12 may monitor user actions only with respect to one or more defined software applications running on themobile device 10. For example, theCAC function 12 may be incorporated into a particular software application and only monitor only those user actions made by the user with respect to that software application. - Based on the monitoring of the user actions taken by the user and the corresponding contexts of the
mobile device 10, theCAC function 12 is enabled to detect correlations between contexts of themobile device 10 and user actions taken by the user of themobile device 10. Each detected correlation between a context and a user action taken by the user of themobile device 10 defines a context of themobile device 10 and a user action that has historically been taken by the user when themobile device 10 is in that context. TheCAC function 12 may then use the stored context-to-user-action correlations to automatically perform user actions in response to detecting the correlated contexts. - The
context sensors 14 may be implemented in hardware, software, or a combination thereof. In general, thecontext sensors 14 are software and/or hardware components that are enabled to obtain data forming the context of themobile device 10. Thecontext sensors 14 preferably include a local wireless communication interface such as, for example, a Bluetooth® communication interface or a communication interface operating according to one of the suite of IEEE 802.11x standards (i.e., a Wi-Fi communication interface). Using the local wireless communication interface, theCAC function 12 is enabled to obtain a list of device IDs ofmobile devices 18 that are located proximate to themobile device 10, user IDs of users of themobile devices 18 that are located proximate to themobile device 10, or a combination thereof. Here, thedevices 18 that are proximate to themobile device 10 aremobile devices 18 that are within a wireless coverage area of themobile device 10 and/ormobile devices 18 for which themobile device 10 is in their wireless coverage areas. Themobile device 10 may obtain the device IDs of themobile devices 18 and/or user IDs of the users of themobile devices 18 by passively monitoring wireless communications to or from themobile devices 18, by actively querying themobile devices 18 for their device IDs or the user IDs of their users, or both. - The
context sensors 14 may also include a software application that interacts with a social networking service (e.g., the Facebook® social networking service) to identify other users in the social network of the user of themobile device 10 that are currently located proximate to themobile device 10. As used herein, a social networking service is also to include an Instant Messaging service or the like. More specifically, in one embodiment, themobile device 10 may query the social networking service via a network connection (e.g., an Internet connection) with the device IDs of themobile devices 18 or the user IDs of the users of themobile devices 18. In this embodiment, the social networking service stores device IDs and/or user IDs for at least some of the users of the social networking service. As such, in response to receiving the query, the social networking service identifies users of the social networking service that correspond to the IDs included in the query, if any, and determines which of the identified users are in the social network of the user of themobile device 10. The social networking service then returns information identifying the users in the social network of the user of themobile device 10 that have IDs matching those of themobile devices 18 or users of themobile devices 18 that are proximate to themobile device 10. In an alternative embodiment, rather than querying the social networking service, themobile device 10 may query an intermediate device or service between themobile device 10 and the social networking service. - In another embodiment, the social networking service tracks locations of users of the social networking service. As such,
CAC function 12 of themobile device 10 may query the social networking service for members of the social network of the user of themobile device 10 that are currently located proximate to the current location of themobile device 10. The social networking service determines which members of the social network of the user of themobile device 10 are proximate to the current location of themobile device 10 and returns information identifying those members to theCAC function 12 at themobile device 10. Here, members of the social network of the user are proximate to the current location of themobile device 10 if, for example, they are within a defined distance from the current location of themobile device 10, at the same street address as themobile device 10, or the like. - Note that, as yet another alternative, a contact list of may be maintained and stored at the
mobile device 10 that include a number of contacts of the user. The contact list may also include device IDs of mobile devices associated with at least some of the contacts. TheCAC function 12 may then use the device IDs of themobile devices 18 and the device IDSs in the contact list to identify other users in the contact list of the user that are currently proximate to themobile device 10. - The
context sensors 14 may also include a location determination function that operates to sense or otherwise obtain the location of themobile device 10. The location determination function may be, but is not limited to, a Global Positioning System (GPS) receiver. Thecontext sensors 14 may also include one ormore context sensors 14 for detecting or otherwise obtaining ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density, or the like. Thecontext sensors 14 may detect the ambient conditions directly or obtain the ambient conditions from a remote device or service (e.g., an Internet based weather service). Further, the one ormore context sensors 14 may include an accelerometer for detecting user or device movement. Still further, thecontext sensors 14 may include a software component for obtaining relevant contextual data from an electronic calendar maintained for the user of themobile device 10, where the electronic calendar may be stored locally at themobile device 10 or remotely by, for example, an Internet based service. - In this embodiment, the
CAC record repository 16 stores a number of CAC records for potential context-to-user-action correlations, which are referred to herein as potential CAC records, and a number of CAC records for actual context-to-user-action correlations, which are referred to herein as actual CAC records. Each CAC record, whether potential or actual, defines a user action and a context of themobile device 10. In addition, the CAC record may include a counter that counts the number of times the defined user action has been detected when themobile device 10 is in the defined context, timestamps defining times at which the defined user action has been detected when themobile device 10 is in the defined context, or both. The CAC record may also include a flag, or indicator, that indicates whether the CAC record is for an actual context-to-user-action correlation or a potential context or user action correlation. -
FIG. 2 is a flow chart illustrating the operation of theCAC function 12 ofFIG. 1 according to one embodiment of the present disclosure. First, theCAC function 12 detects correlations between contexts of themobile device 10 and user actions taken by the user of the mobile device 10 (step 100). More specifically, theCAC function 12 monitors the user actions taken by the user at themobile device 10 and the context of themobile device 10 at the times the user actions were taken. Over time, via results of the monitoring, theCAC function 12 detects correlations between contexts of themobile device 10 and user actions taken by the user of themobile device 10. In general, a context-to-user-action correlation is detected when the user of themobile device 10 has historically performed a particular user action when themobile device 10 is in a particular context. One or more system-defined or user-configurable rules may be used by theCAC function 12 to determine when a context-to-user-action correlation has been detected. For example, theCAC function 12 may detect a context-to-user-action correlation when the user of themobile device 10 has performed a particular user action at themobile device 10 when themobile device 10 is in a particular context, or in a number of matching contexts, at least a defined minimum number of times (e.g., three times). As a specific example, if the user tends to turn the ringer of themobile device 10 off or tends to not take his or her telephone calls while the user is proximate to three or more users while in the user's “work” Wi-Fi network, then theCAC function 12 may detect this as a context-to-user-action correlation. Note that, as used herein, matching contexts are contexts that match exactly or match at least to a predefined threshold degree. As another example, theCAC function 12 may detect a context-to-user-action correlation when the user of themobile device 10 has performed a particular user action at themobile device 10 when themobile device 10 is in a particular context, or in a group of matching contexts, at least a defined minimum number of times (e.g., three times) within a defined amount of time (e.g., one month). Note that the aforementioned examples are illustrative and are not intended to limit the scope of the present disclosure. Other types of rules may be used to detect context-to-user-action correlations. - While the discussion herein focuses on detection of context-to-user-action correlations by the
CAC function 12, the present disclosure is not limited thereto. In one embodiment, in addition to or as an alternative to detection of context-to-user-action correlations by theCAC function 12, theCAC function 12 may enable the user of themobile device 10 to manually define one or more context-to-user-action correlations. These user-defined context-to-user-action correlations may then be used by theCAC function 12 to automatically perform the defined user actions in response to detecting the corresponding contexts in the manner described below. - The CAC function 102 then obtains a current context of the mobile device 10 (step 102). In the preferred embodiment, the current context of the
mobile device 10 includes a list of device IDs of themobile devices 18 currently located proximate to themobile device 10, a list of user IDs for users of themobile devices 18 currently located proximate to themobile device 10, a list of users in a social network of the user of themobile device 10 that are currently proximate to themobile device 10, a list of users in a contact list maintained by themobile device 10 that are proximate to themobile device 10, or a combination thereof. In addition, the current context of themobile device 10 may include a current location of themobile device 10 where the current location of themobile device 10 may be expressed as geospatial coordinates (e.g., latitude and longitude coordinates), a physical address (e.g., a street address), a predefined location designation (e.g., “work” or “home”), Wi-Fi hotspot ID, or the like. Still further, the current context of themobile device 10 may include data defining one or more current ambient conditions such as, for example, temperature, weather conditions, ambient sound level, ambient light level (i.e., visibility), crowd density, or the like. Further, the context of themobile device 10 may include data from an accelerometer that is indicative of user or device movement. Still further, the current context of themobile device 10 may include data obtained from an electronic calendar maintained for the user of themobile device 10 such as an event or meeting that the user is currently scheduled to be attending. - The
CAC function 12 then automatically performs a user action that is correlated to the current context, if any (step 104). In one embodiment, theCAC function 12 automatically performs the user action by first prompting the user of themobile device 10 for approval to perform the user action and then performing the user action upon receiving approval from the user. In another embodiment, theCAC function 12 automatically performs the user action without user interaction from the user of the mobile device 10 (e.g., without first prompting the user for approval). In this embodiment, theCAC function 12 may, after automatically performing the user action, provide an alert to the user indicating that the user action has been taken and why the user action has been taken (e.g., the context that triggered the user action). Note that contexts may be named by the user as part of the context-to-user-action creation process. -
FIGS. 3A through 3C provide a flow chart illustrating the operation of theCAC function 12 ofFIG. 1 in more detail according to one embodiment of the present disclosure. First, theCAC function 12 monitors for a user action (step 200). Again, the user actions monitored for by theCAC function 12 are generally user actions taken by the user of themobile device 10 to interact with themobile device 10. The user actions monitored by theCAC function 12 may be any user action taken by the user to interact with themobile device 10. Alternatively, theCAC function 12 may only monitor for a defined set of user actions taken by the user to interact with the mobile device 10 (e.g., monitor only volume control actions). Further, theCAC function 12 may monitor user actions with respect to themobile device 10 in general. Alternatively, theCAC function 12 may monitor user actions only with respect to one or more defined software applications running on themobile device 10. TheCAC function 12 then determines whether a user action has been detected (step 202). Note that while illustrated separately, steps 200 and 202 may be implemented as a single step. If a user action has been detected, theCAC function 12 obtains the current context of the mobile device 10 (step 204). - Next, the
CAC function 12 determines whether there is a matching CAC record for the current context of the mobile device 10 (step 206). In one embodiment, a matching CAC record is either a potential CAC record or an actual CAC record in theCAC record repository 16 of themobile device 10 having a defined context that matches the current context of themobile device 10 and a defined user action that matches the detected user action fromsteps mobile device 10. The one or more rules may state that, for example, the defined context of the CAC record matches the current context of themobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the CAC record exactly matches the corresponding contextual component of the current context of themobile device 10. As another example, the one or more rules may state that the defined context of the CAC record matches the current context of themobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the CAC record matches the corresponding contextual component of the current context of themobile device 10 to at least a defined threshold degree (e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context). As another example, the one or more rules may state that the defined context of the CAC record matches the current context of themobile device 10 if some contextual components (e.g., list of device IDs) of the defined context for the CAC record match the corresponding contextual components of the current context of themobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of a CAC record are also in the list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the CAC record exactly match the corresponding contextual components of the current context of themobile device 10. - If there is no matching CAC record (referring to step 206), the
CAC function 12 creates a potential CAC record for the current context of themobile device 10 and the detected user action and stores the potential CAC record in the CAC record repository 16 (step 208), and then the process returns to step 200 and is repeated. If there is a matching CAC record, theCAC function 12 determines whether the matching CAC record is an actual CAC record (step 210). If the matching CAC record is not an actual CAC record, the matching CAC record is a potential CAC record. As such, theCAC function 12 then updates the matching potential CAC record to reflect detection of the user action (step 212). More specifically, in one embodiment, the matching potential CAC record includes a counter for the number of times the user action has been detected in the defined context. As such, theCAC function 12 may then increase the counter by a value of one (1). In another embodiment, the matching potential CAC record includes a timestamp for each occurrence of the user action for the defined context. As such, theCAC function 12 may add a timestamp to the matching potential CAC record defining the current time to indicate that the user action was detected with respect to the defined context at the current time. In addition, the defined context of the matching potential CAC record may be updated based on the current context. This is particularly the case where the current context matches the defined context for the matching potential CAC record less than exactly. For example, if the list of device IDs and/or user IDs for the current context does not match the list of device IDs and/or user IDs for the defined context for the matching potential CAC record, any device IDs and/or user IDs in the current context that are not included in the defined context for the matching potential CAC record may be added to the defined context for the matching potential CAC record. Note that, before adding the user IDs to the defined context, this condition may be required to occur a threshold number of times within a defined period of time. - In this embodiment, the
CAC function 12 then determines whether a pattern has been detected for the matching potential CAC record (step 214). In this embodiment, a pattern is detected when the matching potential CAC record indicates that the user of themobile device 10 has historically performed the defined user action when themobile device 10 is in the defined context. One or more system-defined or user-configurable rules may be used by theCAC function 12 to determine when a pattern has been detected. For example, theCAC function 12 may detect a pattern when the number of occurrences for the user action defined by the matching potential CAC record for the context defined by the matching potential CAC record, as indicated by the counter stored in the matching potential CAC record, is greater than a defined threshold number of occurrences (e.g., three times). The defined threshold number of occurrences may be user-defined or system-defined. For instance, in one exemplary embodiment, theCAC function 12 may track the number of times that the user must typically be prompted regarding a potential CAC record before the user approves promoting the potential CAC record to an actual CAC record (see below) and then set the defined threshold number of occurrences to that number. Thus, if the user typically approves promoting potential CAC record to an actual CAC record after being prompted two times, the defined threshold number of occurrences may be set to three. As another example, theCAC function 12 may detect a pattern when a frequency of occurrence for the user action defined by the matching potential CAC record for the context defined by the matching potential CAC record is greater than a defined threshold frequency of occurrence. The frequency of occurrence may be defined from timestamps stored in the matching potential CAC record for occurrences of the defined user action when in the defined context. As an example, the defined threshold frequency of occurrence may be three times over the last month. Note that the aforementioned examples are illustrative and are not intended to limit the scope of the present disclosure. Other types of rules may be used. - If a pattern is not detected, the process returns to step 200 and is repeated. If a pattern is detected, in this embodiment, the
CAC function 12 prompts the user of themobile device 10 for approval to promote the matching potential CAC record to an actual CAC record (step 216). In other words, theCAC function 12 prompts the user of themobile device 10 for approval to promote the matching potential CAC to an actual CAC. TheCAC function 12 then determines whether approval has been received from the user of the mobile device 10 (step 218). If not, the process returns to step 200 and is repeated. If approval is received from the user, theCAC function 12 promotes the matching potential CAC record to an actual CAC record (step 220). In other words, the matching potential CAC is promoted to an actual CAC. In one embodiment, the matching potential CAC record includes a flag indicating that the matching potential CAC record is a potential CAC record. As such, the matching potential CAC record may be promoted to an actual CAC record by setting the flag such that the flag indicates that the matching potential CAC record is now an actual CAC record. In one embodiment, promoting the matching potential CAC record to an actual CAC record may include prompting the user for a name for the actual CAC record or more specifically a name for the context defined by the actual CAC record, which may be used, for example, when displaying alerts. At this point, the process returns to step 200 and is repeated. - Note that steps 216 and 218 are optional. In another embodiment, the user is not prompted for approval. Rather, the matching, potential CAC record is automatically promoted to an actual CAC record without interaction from the user of the
mobile device 10. Further note that whether the user is prompted for approval may be a user configurable setting. - Returning to step 210, if the matching CAC record is an actual CAC record, the
CAC function 12 updates the actual CAC record to reflect the detection of the user action (step 222). In addition, the defined context for the actual CAC record may be updated based on the current context in a manner to that described above. The process then returns to step 200 and is repeated. - Returning to step 202, if a user action is not detected, the
CAC function 12 obtains the current context of the mobile device 10 (step 224) and determines whether there are one or more matching actual CAC records stored in the CAC record repository 16 (step 226). Here, the matching actual CAC records are actual CAC records that define contexts that match the current context of themobile device 10. Again, contexts match if they match exactly or at least a predefined threshold degree. One or more system-defined rules and/or one or more user-configurable rules may be used to determine whether the defined context of an actual CAC record matches the current context of themobile device 10. The one or more rules may state that, for example, the defined context of the actual CAC record matches the current context of themobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the actual CAC record exactly matches the corresponding contextual component of the current context of themobile device 10. As another example, the one or more rules may state that the defined context of the actual CAC record matches the current context of themobile device 10 if each contextual component (e.g., list of device IDs, location, etc.) of the defined context for the actual CAC record matches the corresponding contextual component of the current context of themobile device 10 to at least a defined threshold degree (e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context). As another example, the one or more rules may state that the defined context of the actual CAC record matches the current context of themobile device 10 if some contextual components (e.g., list of device IDs) of the defined context for the actual CAC record match the corresponding contextual components of the current context of themobile device 10 to at least a threshold degree (e.g., at least 90% of device IDs in defined context of CAC record are also in list of device IDs for the current context) and other contextual components (e.g., location) of the defined context for the actual CAC record exactly match the corresponding contextual components of the current context of themobile device 10. - If there are no matching actual CAC records, the process returns to step 200 and is repeated. If there are one or more matching actual CAC records, the
CAC function 12 gets the next matching actual CAC record and the user action defined by the matching actual CAC record (steps 228 and 230). Note that there may be multiple matching actual CAC records where, for example, the user of themobile device 10 has historically taken multiple user actions when in the same context. TheCAC function 12 then prompts the user of themobile device 10 for approval to take the user action defined by the matching actual CAC record (step 232). TheCAC function 12 then determines whether approval has been received from the user (step 234). If approval is not received, the process proceeds to step 238. Note that if approval is not received, theCAC function 12 may record that fact that approval was not received in association with or as part of the CAC record. This information could be used by theCAC function 12 to identify and avoid future false alarms. If approval is received, theCAC function 12 performs the user action defined by the matching actual CAC record (step 236). Note that steps 232 and 234 are optional. In another embodiment, the user is not prompted for approval. Rather, the user action defined by the matching actual CAC record is automatically performed without first prompting for user approval. - In yet another embodiment, approval whether or not approval is requested from the user before performing the user action may be determined by the
CAC function 12 on a case-by-case basis based on user configuration, user-defined or system-defined rules, whether the user has given approval for taking the user action in response to detecting the corresponding context in the past, or whether the user has given approval for taking similar user actions in the past. For example, if the user has always or almost always allowed a user action for turning off a ringer of themobile device 10 when in a “movie theater” context, theCAC function 12 may automatically perform that user action in response to detecting the “movie theater” context without first prompting the user for approval. In contrast, if the user has not consistently turned off the ringer of themobile device 10 when in a “meeting” context, then theCAC function 12 may prompt the user for approval before performing that user action in response to detecting the “meeting” context. - In yet another embodiment, if the user action is performed automatically, the
CAC function 12 may monitor user actions for a short time (e.g., 5-10 seconds) after automatically performing the user action to see if the user reverses the user action. Whether the user reverses the automatically performed user action may then be stored in the CAC record and used by theCAC function 12 to, for example, determine whether to prompt the user for approval before performing the user action in response to detecting the corresponding context in the future. - At this point, whether proceeding from
step CAC function 12 determines whether there are more matching actual CAC records to process (step 238). If so, the process returns to step 228 and is repeated. Once all of the matching actual CAC records have been processed, the process returns to step 200 and is repeated. Note that numerous variations to the process ofFIGS. 3A through 3C will be apparent to one of ordinary skill in the art upon reading this disclosure and are considered within the scope of the present disclosure. For example, steps 228-238 may be modified such that the user is prompted for approval for the user actions defined by all of the matching actual CAC records at once. For instance, the user may be presented with a list of user actions, where the user is enabled to approve any number of the user actions from the list as he or she may desire. Also, along with each user action in the list, the user may be presented with the corresponding context and the contextual components that triggered the inclusion of the user action in the list. The user may then be enabled to edit this list to modify the CAC records for future occurrences. -
FIG. 4 is a block diagram of themobile device 10 according to one embodiment of the present disclosure. As illustrated, themobile device 10 includes acontroller 20 connected tomemory 22, one or moresecondary storage devices 24, one or more communication interfaces 26, one or more user interface components 28, and one ormore context sensors 14 by abus 30 or similar mechanism. Thecontroller 20 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, thecontroller 20 is a microprocessor, and theCAC function 12 is implemented in software and stored in thememory 22 for execution by thecontroller 20. In addition, one or more of thecontext sensors 14 may be implemented in software and stored in thememory 22 for execution by thecontroller 20. The one or moresecondary storage devices 24 are digital storage devices such as, for example, one or more hard disk drives. In one embodiment, theCAC record repository 16 is implemented in the one or moresecondary storage devices 24. The one ormore communication interfaces 26 preferably include a local wireless communication interface such as, but not limited to, a Bluetooth® interface or an IEEE 802.11x interface. In addition, the one ormore communication interfaces 26 may include a cellular telecommunications interface (e.g., GSM, LTE, W-CDMA, WiMAX, or the like). Note that an IEEE 802.11x interface or a cellular telecommunications interface may be utilized to connect to a remote service such as, for example, a social networking service, an Internet based weather service, or the like. Also, note that the local wireless communication interface may be used as, or as part of, one of thecontext sensors 14. The one or more user interface components 28 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof. Note that one or more of the user interface components 28 may be used as, or as part of, one or more of thecontext sensors 14. For example, a microphone user interface component may be used to sense an ambient sound level. Lastly, themobile device 10 may include one or moreadditional context sensors 14 such as, for example, a GPS receiver, or an ambient condition sensor (e.g., a temperature sensor). - Below, a number of exemplary use cases are provided. These use cases are intended to illustrate some but not all of the concepts described above and should not be construed as limiting the scope of the concepts disclosed and claimed herein.
- Use Case #1:
-
- 1. Bob works at an IT company, and is a meeting with Jack, Jim, Dave and Tim.
- 2. During the meeting Bob's wife calls him on his mobile device.
- 3. Bob immediately cancels the call and switches his mobile device to “meeting mode.”
- 4. After about a week, Bob gets a call from a friend while he is again in a meeting with Jack, Jim, Dave and Tim.
- 5. Bob cancels the call again and switches his device to “meeting mode.”
- 6. This time Bob's device automatically scans for any devices within its Bluetooth proximity range and finds the devices of Jack, Jim, Dave and Tim.
- 7. It then identifies/creates a context with these 4 devices.
- 8. The next time when all of these 4 devices are in its proximity range, Bob receives an alert message from his device, “Do you want to switch to meeting mode?”.
- 9. Bob is happy to have received the alert message before the meeting started and accepts it.
- Use Case #2:
-
- 1. Bob goes to a live football game.
- 2. His device scans the wireless environment and finds about 50 devices in its Bluetooth proximity range, of which it recognizes none from Bob's contact list.
- 3. But the device detects that 26 of the 50 devices in its proximity range are tuned to a local internet radio/video station that provides play-by-play audio commentary and video replays of significant plays of the game he is attending. Here, the context of Bob's device includes both the number of devices in its Bluetooth proximity range and the number of those devices tuned to the local internet radio/video station.
- 4. Bob's device identifies the current environment (large density of unknown devices, a majority of those devices tuned to a particular local “channel”) as a “Tar Heels football game” context.
- 5. Bob's device automatically alerts Bob to the appropriate local internet radio/video station that the nearby users are listening to/viewing and tunes to that station upon approval from Bob. Alternatively, Bob's device may automatically tune to the station without approval from Bob.
- Use Case #3:
-
- 1. Bob goes to a movie theatre.
- 2. His device scans the wireless environment and finds about 25 devices in its Bluetooth proximity range, of which it recognizes none from Bob's contact list. It also detects from a light sensor that the ambient lighting is very low.
- 3. The device identifies the current environment (large density of unknown devices, dark surroundings) as a “Movie Theater” context.
- 4. The device automatically switches to “silent mode.”
- Those skilled in the art will recognize improvements and modifications to the preferred embodiments of the present invention. All such improvements and modifications are considered within the scope of the concepts disclosed herein and the claims that follow.
Claims (24)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/764,143 US20120046068A1 (en) | 2009-04-29 | 2010-04-21 | Automatically performing user actions based on detected context-to-user-action correlations |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US17362509P | 2009-04-29 | 2009-04-29 | |
US12/764,143 US20120046068A1 (en) | 2009-04-29 | 2010-04-21 | Automatically performing user actions based on detected context-to-user-action correlations |
Publications (1)
Publication Number | Publication Date |
---|---|
US20120046068A1 true US20120046068A1 (en) | 2012-02-23 |
Family
ID=45594457
Family Applications (8)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/759,749 Abandoned US20120046995A1 (en) | 2009-04-29 | 2010-04-14 | Anonymous crowd comparison |
US12/764,150 Expired - Fee Related US8554770B2 (en) | 2009-04-29 | 2010-04-21 | Profile construction using location-based aggregate profile information |
US12/764,148 Abandoned US20120047565A1 (en) | 2009-04-29 | 2010-04-21 | Proximity-based social graph creation |
US12/764,143 Abandoned US20120046068A1 (en) | 2009-04-29 | 2010-04-21 | Automatically performing user actions based on detected context-to-user-action correlations |
US12/769,031 Abandoned US20120047152A1 (en) | 2009-04-29 | 2010-04-28 | System and method for profile tailoring in an aggregate profiling system |
US12/768,973 Abandoned US20120046017A1 (en) | 2009-04-29 | 2010-04-28 | System and method for prevention of indirect user tracking through aggregate profile data |
US12/769,802 Abandoned US20120047448A1 (en) | 2009-04-29 | 2010-04-29 | System and method for social browsing using aggregated profiles |
US14/037,431 Expired - Fee Related US9053169B2 (en) | 2009-04-29 | 2013-09-26 | Profile construction using location-based aggregate profile information |
Family Applications Before (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/759,749 Abandoned US20120046995A1 (en) | 2009-04-29 | 2010-04-14 | Anonymous crowd comparison |
US12/764,150 Expired - Fee Related US8554770B2 (en) | 2009-04-29 | 2010-04-21 | Profile construction using location-based aggregate profile information |
US12/764,148 Abandoned US20120047565A1 (en) | 2009-04-29 | 2010-04-21 | Proximity-based social graph creation |
Family Applications After (4)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/769,031 Abandoned US20120047152A1 (en) | 2009-04-29 | 2010-04-28 | System and method for profile tailoring in an aggregate profiling system |
US12/768,973 Abandoned US20120046017A1 (en) | 2009-04-29 | 2010-04-28 | System and method for prevention of indirect user tracking through aggregate profile data |
US12/769,802 Abandoned US20120047448A1 (en) | 2009-04-29 | 2010-04-29 | System and method for social browsing using aggregated profiles |
US14/037,431 Expired - Fee Related US9053169B2 (en) | 2009-04-29 | 2013-09-26 | Profile construction using location-based aggregate profile information |
Country Status (1)
Country | Link |
---|---|
US (8) | US20120046995A1 (en) |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110093515A1 (en) * | 2009-10-15 | 2011-04-21 | Mary Elizabeth Albanese | Mobile local search platform |
US20120095979A1 (en) * | 2010-10-15 | 2012-04-19 | Microsoft Corporation | Providing information to users based on context |
US20120102165A1 (en) * | 2010-10-21 | 2012-04-26 | International Business Machines Corporation | Crowdsourcing location based applications and structured data for location based applications |
US20130132566A1 (en) * | 2010-05-11 | 2013-05-23 | Nokia Corporation | Method and apparatus for determining user context |
US20130332410A1 (en) * | 2012-06-07 | 2013-12-12 | Sony Corporation | Information processing apparatus, electronic device, information processing method and program |
WO2014024209A1 (en) * | 2012-08-09 | 2014-02-13 | Tata Consultancy Services Limited | A system and method for measuring the crowdedness of people at a place |
US20140237425A1 (en) * | 2013-02-21 | 2014-08-21 | Yahoo! Inc. | System and method of using context in selecting a response to user device interaction |
US8984151B1 (en) * | 2013-02-05 | 2015-03-17 | Google Inc. | Content developer abuse detection |
WO2017040725A1 (en) * | 2015-08-31 | 2017-03-09 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US20170127259A1 (en) * | 2014-12-29 | 2017-05-04 | Iridium Satellite Llc | Emergency communications from a local area network hotspot |
US9848327B2 (en) | 2010-12-09 | 2017-12-19 | Inmarket Media Llc | Systems, apparatuses, and methods for secure beacon authentication via mobile devices |
US10096041B2 (en) | 2012-07-31 | 2018-10-09 | The Spoken Thought, Inc. | Method of advertising to a targeted buyer |
US10205696B2 (en) * | 2015-06-11 | 2019-02-12 | Avi Solomon | Systems methods circuits and associated computer executable code for facilitating selective messaging and multicasting |
US10346285B2 (en) | 2017-06-09 | 2019-07-09 | Microsoft Technology Licensing, Llc | Instrumentation of user actions in software applications |
US11263399B2 (en) * | 2017-07-31 | 2022-03-01 | Apple Inc. | Correcting input based on user context |
WO2022132328A1 (en) * | 2020-12-14 | 2022-06-23 | Qualcomm Incorporated | Method of sub flow or activity classification |
Families Citing this family (126)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9459622B2 (en) | 2007-01-12 | 2016-10-04 | Legalforce, Inc. | Driverless vehicle commerce network and community |
US9002754B2 (en) | 2006-03-17 | 2015-04-07 | Fatdoor, Inc. | Campaign in a geo-spatial environment |
US9037516B2 (en) | 2006-03-17 | 2015-05-19 | Fatdoor, Inc. | Direct mailing in a geo-spatial environment |
US9064288B2 (en) | 2006-03-17 | 2015-06-23 | Fatdoor, Inc. | Government structures and neighborhood leads in a geo-spatial environment |
US9098545B2 (en) | 2007-07-10 | 2015-08-04 | Raj Abhyanker | Hot news neighborhood banter in a geo-spatial social network |
US9070101B2 (en) | 2007-01-12 | 2015-06-30 | Fatdoor, Inc. | Peer-to-peer neighborhood delivery multi-copter and method |
US9373149B2 (en) | 2006-03-17 | 2016-06-21 | Fatdoor, Inc. | Autonomous neighborhood vehicle commerce network and community |
US8965409B2 (en) | 2006-03-17 | 2015-02-24 | Fatdoor, Inc. | User-generated community publication in an online neighborhood social network |
US8863245B1 (en) | 2006-10-19 | 2014-10-14 | Fatdoor, Inc. | Nextdoor neighborhood social network method, apparatus, and system |
CA2758197A1 (en) * | 2009-04-09 | 2010-10-14 | Aegis Mobility, Inc. | Context based data mediation |
US20120046995A1 (en) | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | Anonymous crowd comparison |
US8775605B2 (en) | 2009-09-29 | 2014-07-08 | At&T Intellectual Property I, L.P. | Method and apparatus to identify outliers in social networks |
US8560608B2 (en) | 2009-11-06 | 2013-10-15 | Waldeck Technology, Llc | Crowd formation based on physical boundaries and other rules |
US20120066303A1 (en) * | 2010-03-03 | 2012-03-15 | Waldeck Technology, Llc | Synchronized group location updates |
US20120023124A1 (en) * | 2010-07-20 | 2012-01-26 | Tobin Biolchini | Social networking communication interface system and method |
KR101742986B1 (en) * | 2010-07-26 | 2017-06-15 | 엘지전자 주식회사 | Image display apparatus and method for operating the same |
US20120035979A1 (en) * | 2010-08-06 | 2012-02-09 | Avaya Inc. | System and method for improving customer service with models for social synchrony and homophily |
US9940682B2 (en) * | 2010-08-11 | 2018-04-10 | Nike, Inc. | Athletic activity user experience and environment |
KR101932714B1 (en) * | 2010-09-28 | 2018-12-26 | 삼성전자주식회사 | Method for creating and joining social group, user device, server, and storage medium thereof |
KR20120034477A (en) * | 2010-10-01 | 2012-04-12 | 엔에이치엔(주) | System and method for providing document based on personal network |
US9460299B2 (en) | 2010-12-09 | 2016-10-04 | Location Labs, Inc. | System and method for monitoring and reporting peer communications |
US9571590B2 (en) * | 2010-12-09 | 2017-02-14 | Location Labs, Inc. | System and method for improved detection and monitoring of online accounts |
US9268956B2 (en) | 2010-12-09 | 2016-02-23 | Location Labs, Inc. | Online-monitoring agent, system, and method for improved detection and monitoring of online accounts |
US20120158503A1 (en) * | 2010-12-17 | 2012-06-21 | Ebay Inc. | Identifying purchase patterns and marketing based on user mood |
US20120209668A1 (en) * | 2011-02-15 | 2012-08-16 | Terry Angelos | Dynamically serving content to social network members |
US8539086B2 (en) | 2011-03-23 | 2013-09-17 | Color Labs, Inc. | User device group formation |
US10034135B1 (en) * | 2011-06-08 | 2018-07-24 | Dstillery Inc. | Privacy-sensitive methods, systems, and media for geo-social targeting |
US20130031160A1 (en) * | 2011-06-27 | 2013-01-31 | Christopher Carmichael | Web 3.0 Content Aggregation, Delivery and Navigation System |
US8775517B1 (en) * | 2011-07-12 | 2014-07-08 | Relationship Science LLC | Viewing connectivity between user and entity of an information service |
US20130204937A1 (en) * | 2011-09-02 | 2013-08-08 | Barry Fernando | Platform for information management and method using same |
US8621019B2 (en) | 2011-09-21 | 2013-12-31 | Color Labs, Inc. | Live content sharing within a social networking environment |
WO2013049922A1 (en) * | 2011-10-05 | 2013-04-11 | WiFarer Inc. | Mobile user profile and preferences from movement patterns |
US20130246595A1 (en) | 2011-10-18 | 2013-09-19 | Hugh O'Donoghue | Method and apparatus for using an organizational structure for generating, using, or updating an enriched user profile |
CN103078781A (en) * | 2011-10-25 | 2013-05-01 | 国际商业机器公司 | Method for instant messaging system and instant messaging system |
US9519722B1 (en) | 2011-11-14 | 2016-12-13 | Google Inc. | Method and system for providing dynamic personalized recommendations for a destination |
US20180253189A1 (en) * | 2011-12-16 | 2018-09-06 | Google Inc. | Controlling display of content |
US20130179263A1 (en) * | 2012-01-11 | 2013-07-11 | Eric Leebow | Contextually linking people to strategic locations |
US8594623B2 (en) * | 2012-01-25 | 2013-11-26 | Telefonaktiebolaget L M Ericsson (Publ) | Subscriber portfolio management system |
US9183597B2 (en) | 2012-02-16 | 2015-11-10 | Location Labs, Inc. | Mobile user classification system and method |
US9195777B2 (en) | 2012-03-07 | 2015-11-24 | Avira B.V. | System, method and computer program product for normalizing data obtained from a plurality of social networks |
US20130254152A1 (en) * | 2012-03-23 | 2013-09-26 | Palo Alto Research Center Incorporated | Distributed system and methods for modeling population-centric activities |
JP6064376B2 (en) | 2012-06-06 | 2017-01-25 | ソニー株式会社 | Information processing device, computer program, and terminal device |
US9412136B2 (en) | 2012-07-09 | 2016-08-09 | Facebook, Inc. | Creation of real-time conversations based on social location information |
TW201408992A (en) * | 2012-08-21 | 2014-03-01 | Hon Hai Prec Ind Co Ltd | Mobile terminal, cloud server, and method for identifying hot spot |
US9712574B2 (en) * | 2012-08-31 | 2017-07-18 | Facebook, Inc. | Real-world view of location-associated social data |
CN104584007B (en) * | 2012-09-06 | 2018-01-09 | 索尼公司 | Message processing device, information processing method and program |
US8925054B2 (en) | 2012-10-08 | 2014-12-30 | Comcast Cable Communications, Llc | Authenticating credentials for mobile platforms |
JP2014106585A (en) * | 2012-11-26 | 2014-06-09 | Sony Corp | Information processing device, terminal device, information processing method and program |
US9026489B2 (en) * | 2012-11-30 | 2015-05-05 | International Business Machines Corporation | Updating a conference invitation responsive to user location |
US9432806B2 (en) * | 2012-12-04 | 2016-08-30 | Ebay Inc. | Dynamic geofence based on members within |
US9104787B2 (en) * | 2012-12-14 | 2015-08-11 | Microsoft Technology Licensing, Llc | Augmenting search results with relevant third-party application content |
US9122759B2 (en) * | 2012-12-18 | 2015-09-01 | Eharmony, Inc. | Systems and methods for online social matchmaking |
US9015110B2 (en) * | 2012-12-20 | 2015-04-21 | Hulu, LLC | Automatic updating of aggregations for aggregating data |
EP2750417A1 (en) * | 2012-12-28 | 2014-07-02 | Telefónica, S.A. | Method for determining points of interest based on user communications and location |
US11025521B1 (en) * | 2013-03-15 | 2021-06-01 | CSC Holdings, LLC | Dynamic sample selection based on geospatial area and selection predicates |
EP2973041B1 (en) | 2013-03-15 | 2018-08-01 | Factual Inc. | Apparatus, systems, and methods for batch and realtime data processing |
US9438685B2 (en) | 2013-03-15 | 2016-09-06 | Location Labs, Inc. | System and method for display of user relationships corresponding to network-enabled communications |
US10367773B2 (en) * | 2013-05-16 | 2019-07-30 | Roger Serad | Social network based on GPS and other network connections |
US9514119B2 (en) * | 2013-05-21 | 2016-12-06 | International Business Machines Corporation | Contributor identification tool |
US9699132B2 (en) * | 2013-05-30 | 2017-07-04 | Tencent Technology (Shenzhen) Company Limited | Method, apparatus, and system for exchanging electronic business card |
DE102013009958A1 (en) * | 2013-06-14 | 2014-12-18 | Sogidia AG | A social networking system and method of exercising it using a computing device that correlates to a user profile |
US20140372197A1 (en) * | 2013-06-14 | 2014-12-18 | Tigerapps | Systems, apparatuses and methods for providing a price point to a consumer for products in an electronic shopping cart of the consumer |
KR20150008688A (en) * | 2013-07-15 | 2015-01-23 | 삼성전자주식회사 | Display apparatus and control method of the same |
US20150039472A1 (en) * | 2013-08-02 | 2015-02-05 | Mark John Tryder | Method and system for selecting and pricing media content |
US10332154B2 (en) * | 2013-10-21 | 2019-06-25 | Shant Tchakerian | Device, method and non-transitory computer readable storage medium for determining a match between profiles |
CN104636354B (en) * | 2013-11-07 | 2018-02-06 | 华为技术有限公司 | A kind of position interest points clustering method and relevant apparatus |
US9635507B2 (en) * | 2013-11-26 | 2017-04-25 | Globalfoundries Inc. | Mobile device analytics |
US20150161649A1 (en) * | 2013-12-10 | 2015-06-11 | Semantic Labs, LLC | Method and system for authorizing and enabling anonymous consumer internet personalization |
WO2015101810A1 (en) * | 2013-12-31 | 2015-07-09 | Turkcell Teknoloji Arastirma Ve Gelistirme A.S. | A system for retrieval and presentation of subscriber density information |
CN104767652B (en) | 2014-01-08 | 2020-01-17 | 杜比实验室特许公司 | Method for monitoring performance of digital transmission environment |
US20150220627A1 (en) * | 2014-02-04 | 2015-08-06 | International Business Machines Corporation | System and method for finding collective interest-based social communities |
US9439367B2 (en) | 2014-02-07 | 2016-09-13 | Arthi Abhyanker | Network enabled gardening with a remotely controllable positioning extension |
US10318990B2 (en) | 2014-04-01 | 2019-06-11 | Ebay Inc. | Selecting users relevant to a geofence |
US10447838B2 (en) | 2014-04-03 | 2019-10-15 | Location Labs, Inc. | Telephone fraud management system and method |
US9936241B2 (en) * | 2014-04-07 | 2018-04-03 | Cellco Partnership | Method and apparatus for providing dynamic channel and content provisioning |
US9457901B2 (en) | 2014-04-22 | 2016-10-04 | Fatdoor, Inc. | Quadcopter with a printable payload extension system and method |
US9004396B1 (en) | 2014-04-24 | 2015-04-14 | Fatdoor, Inc. | Skyteboard quadcopter and method |
CN105095242B (en) | 2014-04-30 | 2018-07-27 | 国际商业机器公司 | A kind of method and apparatus of label geographic area |
US20150317366A1 (en) * | 2014-04-30 | 2015-11-05 | Linkedin Corporation | Generating visual representations of attributes of selected sets of members of a social network |
US9022324B1 (en) | 2014-05-05 | 2015-05-05 | Fatdoor, Inc. | Coordination of aerial vehicles through a central server |
US9473883B2 (en) * | 2014-05-31 | 2016-10-18 | Apple Inc. | Location service authorization and indication |
US9971985B2 (en) | 2014-06-20 | 2018-05-15 | Raj Abhyanker | Train based community |
US9441981B2 (en) | 2014-06-20 | 2016-09-13 | Fatdoor, Inc. | Variable bus stops across a bus route in a regional transportation network |
US9451020B2 (en) | 2014-07-18 | 2016-09-20 | Legalforce, Inc. | Distributed communication of independent autonomous vehicles to provide redundancy and performance |
US10373192B2 (en) * | 2014-08-18 | 2019-08-06 | Google Llc | Matching conversions from applications to selected content items |
US10031925B2 (en) * | 2014-10-15 | 2018-07-24 | Thinkcx Technologies, Inc. | Method and system of using image recognition and geolocation signal analysis in the construction of a social media user identity graph |
CN105681007B (en) * | 2014-11-19 | 2020-11-06 | 北京三星通信技术研究有限公司 | Reference signal sending and receiving method and device, and scheduling method and device |
EP3030020B1 (en) * | 2014-12-01 | 2020-01-08 | Viavi Solutions UK Limited | Providing streaming geolocation infomation |
CN105824840B (en) | 2015-01-07 | 2019-07-16 | 阿里巴巴集团控股有限公司 | A kind of method and device for area label management |
WO2016123266A1 (en) * | 2015-01-27 | 2016-08-04 | Twitter, Inc. | Capture and sharing of video contents |
US10223397B1 (en) * | 2015-03-13 | 2019-03-05 | Snap Inc. | Social graph based co-location of network users |
US9665733B1 (en) * | 2015-03-31 | 2017-05-30 | Google Inc. | Setting access controls for a content item |
US10200808B2 (en) * | 2015-04-14 | 2019-02-05 | At&T Mobility Ii Llc | Anonymization of location datasets for travel studies |
CN106294516A (en) * | 2015-06-12 | 2017-01-04 | 阿里巴巴集团控股有限公司 | Method for providing position information and device |
EP3107319A1 (en) | 2015-06-17 | 2016-12-21 | a French Société par Actions Simplifiée Facetts | User network system with selective user facet connections |
US9900392B2 (en) * | 2015-06-25 | 2018-02-20 | Facebook, Inc. | Identifying groups for recommendation to a social networking system user based on user location and locations associated with groups |
US10268773B2 (en) | 2015-06-30 | 2019-04-23 | International Business Machines Corporation | Navigating a website using visual analytics and a dynamic data source |
EP3139572A1 (en) * | 2015-09-07 | 2017-03-08 | Alcatel Lucent | User profiling for location based advertising |
US9953176B2 (en) * | 2015-10-02 | 2018-04-24 | Dtex Systems Inc. | Method and system for anonymizing activity records |
US9723441B2 (en) * | 2015-10-06 | 2017-08-01 | International Business Machines Corporation | Location based on call detail record |
US9930134B2 (en) * | 2015-11-25 | 2018-03-27 | International Business Machines Corporation | File replication on location-aware devices |
US9928512B2 (en) | 2015-11-25 | 2018-03-27 | International Business Machines Corporation | Intelligent detection of changed user parameters in a system |
CA3009851C (en) * | 2016-03-01 | 2019-04-09 | Nandbox Inc. | Managing multiple profiles for a single account in an asynchronous messaging system |
US10489401B2 (en) | 2016-05-31 | 2019-11-26 | International Business Machines Corporation | Efficient aggregation in a parallel system |
US11934450B2 (en) * | 2016-06-24 | 2024-03-19 | Skusub LLC | System and method for object matching using 3D imaging |
CN107666500B (en) * | 2016-07-28 | 2021-01-15 | 腾讯科技(深圳)有限公司 | Timing method, device and system |
EP3322149B1 (en) * | 2016-11-10 | 2023-09-13 | Tata Consultancy Services Limited | Customized map generation with real time messages and locations from concurrent users |
US10542019B2 (en) * | 2017-03-09 | 2020-01-21 | International Business Machines Corporation | Preventing intersection attacks |
US20180330325A1 (en) | 2017-05-12 | 2018-11-15 | Zippy Inc. | Method for indicating delivery location and software for same |
CN107360146B (en) * | 2017-07-03 | 2021-03-26 | 深圳大学 | Privacy protection space crowdsourcing task allocation system and method for receiving guarantee |
TWI644224B (en) * | 2017-10-18 | 2018-12-11 | 財團法人工業技術研究院 | Data de-identification method, data de-identification apparatus and non-transitory computer readable storage medium executing the same |
US10629242B2 (en) * | 2017-12-06 | 2020-04-21 | International Business Machines Corporation | Recording user activity on a computer |
US11068511B2 (en) | 2018-03-27 | 2021-07-20 | International Business Machines Corporation | Aggregate relationship graph |
CN110390045B (en) * | 2018-04-12 | 2021-12-17 | 腾讯大地通途(北京)科技有限公司 | Interest point recommendation method and device based on location service |
US11463441B2 (en) | 2018-05-24 | 2022-10-04 | People.ai, Inc. | Systems and methods for managing the generation or deletion of record objects based on electronic activities and communication policies |
US10565229B2 (en) | 2018-05-24 | 2020-02-18 | People.ai, Inc. | Systems and methods for matching electronic activities directly to record objects of systems of record |
US11924297B2 (en) | 2018-05-24 | 2024-03-05 | People.ai, Inc. | Systems and methods for generating a filtered data set |
WO2019231439A1 (en) * | 2018-05-30 | 2019-12-05 | Google Llc | Optimizing geographic region selection |
CN110634208A (en) | 2018-06-22 | 2019-12-31 | 开利公司 | Zone learning for friction-free building interaction |
US11017430B2 (en) * | 2018-11-16 | 2021-05-25 | International Business Machines Corporation | Delivering advertisements based on user sentiment and learned behavior |
US11468029B2 (en) * | 2019-01-21 | 2022-10-11 | Netapp, Inc. | Evolution of communities derived from access patterns |
CN111291082B (en) * | 2020-01-20 | 2023-10-31 | 北京百度网讯科技有限公司 | Data aggregation processing method, device, equipment and storage medium |
US10976979B1 (en) * | 2020-03-20 | 2021-04-13 | Facebook Technologies, Llc | Social experiences in artificial reality environments |
US20220092658A1 (en) * | 2020-09-22 | 2022-03-24 | Gopesh Kumar | System and method for expert service providers to provide one on one chat advice services through unique empowered independent agents to consumers |
US11477615B2 (en) * | 2020-10-30 | 2022-10-18 | Hewlett Packard Enterprise Development Lp | Alerting mobile devices based on location and duration data |
CN116783894A (en) * | 2021-01-25 | 2023-09-19 | 埃美杰斯有限责任公司 | Method and system for reconciling uncoordinated content by data filtering and synchronization based on multi-modal metadata to generate a composite media asset |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6128412A (en) * | 1996-09-02 | 2000-10-03 | Fujitsu Limited | Statistical data compression/decompression method |
US20020083025A1 (en) * | 1998-12-18 | 2002-06-27 | Robarts James O. | Contextual responses based on automated learning techniques |
US20030235173A1 (en) * | 2002-06-24 | 2003-12-25 | Intel Corporation | Call routing in a location-aware network |
US20050227676A1 (en) * | 2000-07-27 | 2005-10-13 | Microsoft Corporation | Place specific buddy list services |
US7054614B1 (en) * | 2000-08-07 | 2006-05-30 | Denso Corporation | Context privacy for delivery of context-aware content for wireless terminals |
US20080005651A1 (en) * | 2001-08-13 | 2008-01-03 | Xerox Corporation | System for automatically generating queries |
US20080082465A1 (en) * | 2006-09-28 | 2008-04-03 | Microsoft Corporation | Guardian angel |
US7424541B2 (en) * | 2004-02-09 | 2008-09-09 | Proxpro, Inc. | Method and computer system for matching mobile device users for business and social networking |
US20090013052A1 (en) * | 1998-12-18 | 2009-01-08 | Microsoft Corporation | Automated selection of appropriate information based on a computer user's context |
US20090036102A1 (en) * | 2007-07-30 | 2009-02-05 | Sybase, Inc. | Context-Based Data Pre-Fetching and Notification for Mobile Applications |
US20100082512A1 (en) * | 2008-09-29 | 2010-04-01 | Microsoft Corporation | Analyzing data and providing recommendations |
US20130185750A1 (en) * | 2012-01-17 | 2013-07-18 | General Instrument Corporation | Context based correlative targeted advertising |
Family Cites Families (182)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5539232A (en) | 1994-05-31 | 1996-07-23 | Kabushiki Kaisha Toshiba | MOS composite type semiconductor device |
US5758257A (en) * | 1994-11-29 | 1998-05-26 | Herz; Frederick | System and method for scheduling broadcast of and access to video programs and other data using customer profiles |
US5734721A (en) * | 1995-10-12 | 1998-03-31 | Itt Corporation | Anti-spoof without error extension (ANSWER) |
US6308175B1 (en) * | 1996-04-04 | 2001-10-23 | Lycos, Inc. | Integrated collaborative/content-based filter structure employing selectively shared, content-based profile data to evaluate information entities in a massive information network |
US5890152A (en) | 1996-09-09 | 1999-03-30 | Seymour Alvin Rapaport | Personal feedback browser for obtaining media files |
US20010013009A1 (en) | 1997-05-20 | 2001-08-09 | Daniel R. Greening | System and method for computer-based marketing |
US6189008B1 (en) | 1998-04-03 | 2001-02-13 | Intertainer, Inc. | Dynamic digital asset management |
US6240069B1 (en) | 1998-06-16 | 2001-05-29 | Ericsson Inc. | System and method for location-based group services |
US6209111B1 (en) * | 1998-11-09 | 2001-03-27 | Microsoft Corporation | Error correction on a mobile device |
US6385619B1 (en) | 1999-01-08 | 2002-05-07 | International Business Machines Corporation | Automatic user interest profile generation from structured document access information |
US6401051B1 (en) | 1999-04-20 | 2002-06-04 | Sun Microsystems, Inc. | Method and apparatus for locating buried objects |
US7162471B1 (en) | 1999-05-11 | 2007-01-09 | Maquis Techtrix Llc | Content query system and method |
US20040181668A1 (en) | 1999-06-30 | 2004-09-16 | Blew Edwin O. | Methods for conducting server-side encryption/decryption-on-demand |
US6549768B1 (en) | 1999-08-24 | 2003-04-15 | Nokia Corp | Mobile communications matching system |
ATE253283T1 (en) | 1999-09-29 | 2003-11-15 | Swisscom Mobile Ag | METHOD FOR FINDING MEMBERS OF A COMMON INTEREST GROUP |
WO2001025947A1 (en) * | 1999-10-04 | 2001-04-12 | Meidar Liad Y | Method of dynamically recommending web sites and answering user queries based upon affinity groups |
US6204844B1 (en) | 1999-10-08 | 2001-03-20 | Motorola, Inc. | Method and apparatus for dynamically grouping communication units in a communication system |
US6724403B1 (en) * | 1999-10-29 | 2004-04-20 | Surfcast, Inc. | System and method for simultaneous display of multiple information sources |
US6819919B1 (en) | 1999-10-29 | 2004-11-16 | Telcontar | Method for providing matching and introduction services to proximate mobile users and service providers |
US6708172B1 (en) | 1999-12-22 | 2004-03-16 | Urbanpixel, Inc. | Community-based shared multiple browser environment |
GB2358263A (en) | 2000-01-13 | 2001-07-18 | Applied Psychology Res Ltd | Generating user profile data |
CA2298194A1 (en) | 2000-02-07 | 2001-08-07 | Profilium Inc. | Method and system for delivering and targeting advertisements over wireless networks |
US6701362B1 (en) | 2000-02-23 | 2004-03-02 | Purpleyogi.Com Inc. | Method for creating user profiles |
US20020010628A1 (en) | 2000-05-24 | 2002-01-24 | Alan Burns | Method of advertising and polling |
US6539232B2 (en) | 2000-06-10 | 2003-03-25 | Telcontar | Method and system for connecting mobile users based on degree of separation |
US20020049690A1 (en) | 2000-06-16 | 2002-04-25 | Masanori Takano | Method of expressing crowd movement in game, storage medium, and information processing apparatus |
US8117281B2 (en) | 2006-11-02 | 2012-02-14 | Addnclick, Inc. | Using internet content as a means to establish live social networks by linking internet users to each other who are simultaneously engaged in the same and/or similar content |
EP1336143B1 (en) * | 2000-11-20 | 2004-06-09 | BRITISH TELECOMMUNICATIONS public limited company | Information provider |
US6832242B2 (en) | 2000-12-28 | 2004-12-14 | Intel Corporation | System and method for automatically sharing information between handheld devices |
US7062469B2 (en) | 2001-01-02 | 2006-06-13 | Nokia Corporation | System and method for public wireless network access subsidized by dynamic display advertising |
US6529136B2 (en) | 2001-02-28 | 2003-03-04 | International Business Machines Corporation | Group notification system and method for implementing and indicating the proximity of individuals or groups to other individuals or groups |
US20040098386A1 (en) | 2001-03-30 | 2004-05-20 | Marcus Thint | Profile management system |
US6757517B2 (en) | 2001-05-10 | 2004-06-29 | Chin-Chi Chang | Apparatus and method for coordinated music playback in wireless ad-hoc networks |
JP2003203084A (en) | 2001-06-29 | 2003-07-18 | Hitachi Ltd | Information terminal device, server, and information distributing device and method |
US7123918B1 (en) | 2001-08-20 | 2006-10-17 | Verizon Services Corp. | Methods and apparatus for extrapolating person and device counts |
US20050231425A1 (en) | 2001-09-10 | 2005-10-20 | American Gnc Corporation | Wireless wide area networked precision geolocation |
US7035863B2 (en) | 2001-11-13 | 2006-04-25 | Koninklijke Philips Electronics N.V. | Method, system and program product for populating a user profile based on existing user profiles |
US20040025185A1 (en) | 2002-04-29 | 2004-02-05 | John Goci | Digital video jukebox network enterprise system |
US7024207B2 (en) | 2002-04-30 | 2006-04-04 | Motorola, Inc. | Method of targeting a message to a communication device selected from among a set of communication devices |
US7403990B2 (en) | 2002-05-08 | 2008-07-22 | Ricoh Company, Ltd. | Information distribution system |
US7254406B2 (en) | 2002-06-10 | 2007-08-07 | Suman Beros | Method and apparatus for effecting a detection of mobile devices that are proximate and exhibit commonalities between specific data sets, or profiles, associated with the persons transporting the mobile devices |
US7444655B2 (en) | 2002-06-11 | 2008-10-28 | Microsoft Corporation | Anonymous aggregated data collection |
US7116985B2 (en) | 2002-06-14 | 2006-10-03 | Cingular Wireless Ii, Llc | Method for providing location-based services in a wireless network, such as varying levels of services |
JP2004133733A (en) * | 2002-10-11 | 2004-04-30 | Sony Corp | Display device, display method, and program |
US20040098744A1 (en) | 2002-11-18 | 2004-05-20 | Koninklijke Philips Electronics N.V. | Creation of a stereotypical profile via image based clustering |
US7247024B2 (en) | 2002-11-22 | 2007-07-24 | Ut-Battelle, Llc | Method for spatially distributing a population |
US8375008B1 (en) * | 2003-01-17 | 2013-02-12 | Robert Gomes | Method and system for enterprise-wide retention of digital or electronic data |
JP2004241866A (en) | 2003-02-03 | 2004-08-26 | Alpine Electronics Inc | Inter-vehicle communication system |
US8423042B2 (en) | 2004-02-24 | 2013-04-16 | Invisitrack, Inc. | Method and system for positional finding using RF, continuous and/or combined movement |
US7787886B2 (en) | 2003-02-24 | 2010-08-31 | Invisitrack, Inc. | System and method for locating a target using RFID |
US7158798B2 (en) | 2003-02-28 | 2007-01-02 | Lucent Technologies Inc. | Location-based ad-hoc game services |
FI118494B (en) | 2003-03-26 | 2007-11-30 | Teliasonera Finland Oyj | A method for monitoring traffic flows of mobile users |
GB2402841B (en) * | 2003-06-10 | 2005-05-11 | Whereonearth Ltd | A method of providing location based information to a mobile terminal within a communications network |
JP4705576B2 (en) | 2003-06-12 | 2011-06-22 | 本田技研工業株式会社 | System and method for determining the number of people in a crowd using Visualhall |
US20050038876A1 (en) | 2003-08-15 | 2005-02-17 | Aloke Chaudhuri | System and method for instant match based on location, presence, personalization and communication |
US7428417B2 (en) | 2003-09-26 | 2008-09-23 | Siemens Communications, Inc. | System and method for presence perimeter rule downloading |
US20040107283A1 (en) | 2003-10-06 | 2004-06-03 | Trilibis Inc. | System and method for the aggregation and matching of personal information |
US20050130634A1 (en) | 2003-10-31 | 2005-06-16 | Globespanvirata, Inc. | Location awareness in wireless networks |
US7359724B2 (en) | 2003-11-20 | 2008-04-15 | Nokia Corporation | Method and system for location based group formation |
US20070162328A1 (en) | 2004-01-20 | 2007-07-12 | Nooly Technologies, Ltd. | Lbs nowcasting sensitive advertising and promotion system and method |
US7398081B2 (en) | 2004-02-04 | 2008-07-08 | Modu Ltd. | Device and system for selective wireless communication with contact list memory |
US7545784B2 (en) | 2004-02-11 | 2009-06-09 | Yahoo! Inc. | System and method for wireless communication between previously known and unknown users |
US8014763B2 (en) | 2004-02-28 | 2011-09-06 | Charles Martin Hymes | Wireless communications with proximal targets identified visually, aurally, or positionally |
US7593740B2 (en) | 2004-05-12 | 2009-09-22 | Google, Inc. | Location-based social software for mobile devices |
US20050278317A1 (en) | 2004-05-14 | 2005-12-15 | William Gross | Personalized search engine |
JP4660475B2 (en) | 2004-06-10 | 2011-03-30 | パナソニック株式会社 | User profile management system |
US7509131B2 (en) | 2004-06-29 | 2009-03-24 | Microsoft Corporation | Proximity detection using wireless signal strengths |
US8078607B2 (en) * | 2006-03-30 | 2011-12-13 | Google Inc. | Generating website profiles based on queries from webistes and user activities on the search results |
US20060036457A1 (en) * | 2004-08-13 | 2006-02-16 | Mcnamara Lori | Systems and methods for facilitating romantic connections |
US20060046743A1 (en) | 2004-08-24 | 2006-03-02 | Mirho Charles A | Group organization according to device location |
US8126441B2 (en) | 2004-09-21 | 2012-02-28 | Advanced Ground Information Systems, Inc. | Method of establishing a cell phone network of participants with a common interest |
US11283885B2 (en) | 2004-10-19 | 2022-03-22 | Verizon Patent And Licensing Inc. | System and method for location based matching and promotion |
WO2006044939A2 (en) * | 2004-10-19 | 2006-04-27 | Rosen James S | System and method for location based social networking |
US7707413B2 (en) | 2004-12-02 | 2010-04-27 | Palo Alto Research Center Incorporated | Systems and methods for protecting private information in a mobile environment |
US20060123080A1 (en) | 2004-12-03 | 2006-06-08 | Motorola, Inc. | Method and system of collectively setting preferences among a plurality of electronic devices and users |
US20060229058A1 (en) | 2005-10-29 | 2006-10-12 | Outland Research | Real-time person-to-person communication using geospatial addressing |
US20060195361A1 (en) | 2005-10-01 | 2006-08-31 | Outland Research | Location-based demographic profiling system and method of use |
US7853268B2 (en) | 2005-01-26 | 2010-12-14 | Broadcom Corporation | GPS enabled cell phone location tracking for security purposes |
JP4630080B2 (en) * | 2005-01-31 | 2011-02-09 | 富士通株式会社 | Data restoration method and data restoration program |
US7236091B2 (en) * | 2005-02-10 | 2007-06-26 | Pinc Solutions | Position-tracking system |
US7423580B2 (en) | 2005-03-14 | 2008-09-09 | Invisitrack, Inc. | Method and system of three-dimensional positional finding |
US8060463B1 (en) * | 2005-03-30 | 2011-11-15 | Amazon Technologies, Inc. | Mining of user event data to identify users with common interests |
US7353034B2 (en) | 2005-04-04 | 2008-04-01 | X One, Inc. | Location sharing and tracking using mobile phones or other wireless devices |
US20070210937A1 (en) | 2005-04-21 | 2007-09-13 | Microsoft Corporation | Dynamic rendering of map information |
US20060282303A1 (en) | 2005-06-08 | 2006-12-14 | Microsoft Corporation | Distributed organizational analyzer |
US7908254B2 (en) * | 2005-06-10 | 2011-03-15 | Hewlett-Packard Development Company, L.P. | Identifying characteristics in sets of organized items |
US20070005419A1 (en) * | 2005-06-30 | 2007-01-04 | Microsoft Corporation | Recommending location and services via geospatial collaborative filtering |
US20070156664A1 (en) | 2005-07-06 | 2007-07-05 | Gemini Mobile Technologies, Inc. | Automatic user matching in an online environment |
US20070015518A1 (en) | 2005-07-15 | 2007-01-18 | Agilis Systems, Inc. | Mobile resource location-based customer contact systems |
US8150416B2 (en) | 2005-08-08 | 2012-04-03 | Jambo Networks, Inc. | System and method for providing communication services to mobile device users incorporating proximity determination |
WO2007026357A2 (en) * | 2005-08-30 | 2007-03-08 | Nds Limited | Enhanced electronic program guides |
US7734632B2 (en) * | 2005-10-28 | 2010-06-08 | Disney Enterprises, Inc. | System and method for targeted ad delivery |
CN1967523B (en) | 2005-11-15 | 2010-07-28 | 日电(中国)有限公司 | Inquiry system and method of traffic information |
US20070118509A1 (en) | 2005-11-18 | 2007-05-24 | Flashpoint Technology, Inc. | Collaborative service for suggesting media keywords based on location data |
KR101375583B1 (en) | 2005-11-23 | 2014-04-01 | 오브젝트비디오 인코퍼레이티드 | Object Density Estimation in Video |
US7558404B2 (en) | 2005-11-28 | 2009-07-07 | Honeywell International Inc. | Detection of abnormal crowd behavior |
US20070135138A1 (en) | 2005-12-13 | 2007-06-14 | Internation Business Machines Corporation | Methods, systems, and computer program products for providing location based subscription services |
US20070149214A1 (en) | 2005-12-13 | 2007-06-28 | Squareloop, Inc. | System, apparatus, and methods for location managed message processing |
US7774001B2 (en) | 2005-12-16 | 2010-08-10 | Sony Ericsson Mobile Communications Ab | Device and method for determining where crowds exist |
US7801542B1 (en) | 2005-12-19 | 2010-09-21 | Stewart Brett B | Automatic management of geographic information pertaining to social networks, groups of users, or assets |
US7620404B2 (en) | 2005-12-22 | 2009-11-17 | Pascal Chesnais | Methods and apparatus for organizing and presenting contact information in a mobile communication system |
US20070218900A1 (en) | 2006-03-17 | 2007-09-20 | Raj Vasant Abhyanker | Map based neighborhood search and community contribution |
KR100750632B1 (en) | 2005-12-30 | 2007-08-20 | 삼성전자주식회사 | Interactive traffic information providing method and apparatus |
US7466986B2 (en) | 2006-01-19 | 2008-12-16 | International Business Machines Corporation | On-device mapping of WIFI hotspots via direct connection of WIFI-enabled and GPS-enabled mobile devices |
US20070174243A1 (en) | 2006-01-20 | 2007-07-26 | Fritz Charles W | Mobile social search using physical identifiers |
US20070179863A1 (en) | 2006-01-30 | 2007-08-02 | Goseetell Network, Inc. | Collective intelligence recommender system for travel information and travel industry marketing platform |
US7788188B2 (en) | 2006-01-30 | 2010-08-31 | Hoozware, Inc. | System for providing a service to venues where people aggregate |
WO2007090133A2 (en) | 2006-01-30 | 2007-08-09 | Kramer Jame F | System for providing a service to venues where people aggregate |
US8352183B2 (en) | 2006-02-04 | 2013-01-08 | Microsoft Corporation | Maps for social networking and geo blogs |
US8046411B2 (en) | 2006-04-28 | 2011-10-25 | Yahoo! Inc. | Multimedia sharing in social networks for mobile devices |
US20070282621A1 (en) | 2006-06-01 | 2007-12-06 | Flipt, Inc | Mobile dating system incorporating user location information |
US20070290832A1 (en) | 2006-06-16 | 2007-12-20 | Fmr Corp. | Invoking actionable alerts |
US7673327B1 (en) * | 2006-06-27 | 2010-03-02 | Confluence Commons, Inc. | Aggregation system |
US7552862B2 (en) | 2006-06-29 | 2009-06-30 | Microsoft Corporation | User-controlled profile sharing |
WO2008000043A1 (en) | 2006-06-30 | 2008-01-03 | Eccosphere International Pty Ltd | Method of social interaction between communication device users |
US7685192B1 (en) | 2006-06-30 | 2010-03-23 | Amazon Technologies, Inc. | Method and system for displaying interest space user communities |
US7680959B2 (en) | 2006-07-11 | 2010-03-16 | Napo Enterprises, Llc | P2P network for providing real time media recommendations |
US7932831B2 (en) | 2006-07-11 | 2011-04-26 | At&T Intellectual Property I, L.P. | Crowd determination |
US20080059492A1 (en) * | 2006-08-31 | 2008-03-06 | Tarin Stephen A | Systems, methods, and storage structures for cached databases |
US20080182563A1 (en) | 2006-09-15 | 2008-07-31 | Wugofski Theodore D | Method and system for social networking over mobile devices using profiles |
US8117210B2 (en) * | 2006-10-06 | 2012-02-14 | Eastman Kodak Company | Sampling image records from a collection based on a change metric |
US20080086741A1 (en) | 2006-10-10 | 2008-04-10 | Quantcast Corporation | Audience commonality and measurement |
US20080097999A1 (en) | 2006-10-10 | 2008-04-24 | Tim Horan | Dynamic creation of information sharing social networks |
US20080113674A1 (en) | 2006-11-10 | 2008-05-15 | Mohammad Faisal Baig | Vicinity-based community for wireless users |
US7849082B2 (en) | 2006-11-17 | 2010-12-07 | W.W. Grainger, Inc. | System and method for influencing display of web site content |
US8116564B2 (en) | 2006-11-22 | 2012-02-14 | Regents Of The University Of Minnesota | Crowd counting and monitoring |
US20080242317A1 (en) | 2007-03-26 | 2008-10-02 | Fatdoor, Inc. | Mobile content creation, sharing, and commerce in a geo-spatial environment |
US20080126113A1 (en) | 2006-11-29 | 2008-05-29 | Steve Manning | Systems and methods for creating and participating in ad-hoc virtual communities |
US8108414B2 (en) | 2006-11-29 | 2012-01-31 | David Stackpole | Dynamic location-based social networking |
US7630972B2 (en) * | 2007-01-05 | 2009-12-08 | Yahoo! Inc. | Clustered search processing |
US8954500B2 (en) * | 2008-01-04 | 2015-02-10 | Yahoo! Inc. | Identifying and employing social network relationships |
US20080182591A1 (en) | 2006-12-13 | 2008-07-31 | Synthesis Studios, Inc. | Mobile Proximity-Based Notifications |
US20080146250A1 (en) | 2006-12-15 | 2008-06-19 | Jeffrey Aaron | Method and System for Creating and Using a Location Safety Indicator |
US8224359B2 (en) | 2006-12-22 | 2012-07-17 | Yahoo! Inc. | Provisioning my status information to others in my social network |
US20080188261A1 (en) | 2007-02-02 | 2008-08-07 | Miles Arnone | Mediated social network |
US8112720B2 (en) | 2007-04-05 | 2012-02-07 | Napo Enterprises, Llc | System and method for automatically and graphically associating programmatically-generated media item recommendations related to a user's socially recommended media items |
US9140552B2 (en) | 2008-07-02 | 2015-09-22 | Qualcomm Incorporated | User defined names for displaying monitored location |
US20080261569A1 (en) * | 2007-04-23 | 2008-10-23 | Helio, Llc | Integrated messaging, contacts, and mail interface, systems and methods |
WO2008147252A1 (en) | 2007-05-28 | 2008-12-04 | Telefonaktiebolaget Lm Ericsson (Publ) | A method and apparatus for providing services to client groups in a communication network |
US8185137B2 (en) | 2007-06-25 | 2012-05-22 | Microsoft Corporation | Intensity-based maps |
US20090006551A1 (en) * | 2007-06-29 | 2009-01-01 | Microsoft Corporation | Dynamic awareness of people |
US20090048977A1 (en) * | 2007-07-07 | 2009-02-19 | Qualcomm Incorporated | User profile generation architecture for targeted content distribution using external processes |
US8165808B2 (en) | 2007-07-17 | 2012-04-24 | Yahoo! Inc. | Techniques for representing location information |
US7962155B2 (en) | 2007-07-18 | 2011-06-14 | Hewlett-Packard Development Company, L.P. | Location awareness of devices |
US20090030999A1 (en) | 2007-07-27 | 2009-01-29 | Gatzke Alan D | Contact Proximity Notification |
EP2176730A4 (en) | 2007-08-08 | 2011-04-20 | Baynote Inc | Method and apparatus for context-based content recommendation |
US8050690B2 (en) | 2007-08-14 | 2011-11-01 | Mpanion, Inc. | Location based presence and privacy management |
US8924250B2 (en) | 2007-09-13 | 2014-12-30 | International Business Machines Corporation | Advertising in virtual environments based on crowd statistics |
US7958142B2 (en) * | 2007-09-20 | 2011-06-07 | Microsoft Corporation | User profile aggregation |
US8923887B2 (en) | 2007-09-24 | 2014-12-30 | Alcatel Lucent | Social networking on a wireless communication system |
JP4858400B2 (en) | 2007-10-17 | 2012-01-18 | ソニー株式会社 | Information providing system, information providing apparatus, and information providing method |
US20090106040A1 (en) | 2007-10-23 | 2009-04-23 | New Jersey Institute Of Technology | System And Method For Synchronous Recommendations of Social Interaction Spaces to Individuals |
US7904442B2 (en) * | 2007-10-31 | 2011-03-08 | Intuit Inc. | Method and apparatus for facilitating a collaborative search procedure |
US8467955B2 (en) | 2007-10-31 | 2013-06-18 | Microsoft Corporation | Map-centric service for social events |
US8624733B2 (en) | 2007-11-05 | 2014-01-07 | Francis John Cusack, JR. | Device for electronic access control with integrated surveillance |
US8620996B2 (en) | 2007-11-19 | 2013-12-31 | Motorola Mobility Llc | Method and apparatus for determining a group preference in a social network |
US9269089B2 (en) | 2007-11-22 | 2016-02-23 | Yahoo! Inc. | Method and system for media promotion |
US20100020776A1 (en) | 2007-11-27 | 2010-01-28 | Google Inc. | Wireless network-based location approximation |
US7895049B2 (en) | 2007-11-30 | 2011-02-22 | Yahoo! Inc. | Dynamic representation of group activity through reactive personas |
US8862622B2 (en) | 2007-12-10 | 2014-10-14 | Sprylogics International Corp. | Analysis, inference, and visualization of social networks |
US8307029B2 (en) | 2007-12-10 | 2012-11-06 | Yahoo! Inc. | System and method for conditional delivery of messages |
US8010601B2 (en) | 2007-12-21 | 2011-08-30 | Waldeck Technology, Llc | Contiguous location-based user networks |
US8060018B2 (en) | 2008-02-08 | 2011-11-15 | Yahoo! Inc. | Data sharing based on proximity-based ad hoc network |
US20090210480A1 (en) | 2008-02-14 | 2009-08-20 | Suthaharan Sivasubramaniam | Method and system for collective socializing using a mobile social network |
US20090209286A1 (en) | 2008-02-19 | 2009-08-20 | Motorola, Inc. | Aggregated view of local and remote social information |
CA2657495C (en) * | 2008-03-10 | 2017-04-18 | Careerious | System and method for creating a dynamic customized employment profile and subsequent use thereof |
WO2009146130A2 (en) * | 2008-04-05 | 2009-12-03 | Social Communications Company | Shared virtual area communication environment based apparatus and methods |
US9646025B2 (en) * | 2008-05-27 | 2017-05-09 | Qualcomm Incorporated | Method and apparatus for aggregating and presenting data associated with geographic locations |
US20090307263A1 (en) * | 2008-06-06 | 2009-12-10 | Sense Networks, Inc. | System And Method Of Performing Location Analytics |
US8214346B2 (en) * | 2008-06-27 | 2012-07-03 | Cbs Interactive Inc. | Personalization engine for classifying unstructured documents |
US20100017261A1 (en) | 2008-07-17 | 2010-01-21 | Kota Enterprises, Llc | Expert system and service for location-based content influence for narrowcast |
US8812361B2 (en) | 2008-07-24 | 2014-08-19 | At&T Intellectual Properties I, L.P. | System and method of targeted advertisement |
US20100041378A1 (en) * | 2008-08-14 | 2010-02-18 | Ralph Aceves | System and method for automatically generating a user profile from location information |
US20100064253A1 (en) * | 2008-09-11 | 2010-03-11 | International Business Machines Corporation | Providing Users With Location Information Within a Virtual World |
US8645283B2 (en) | 2008-11-24 | 2014-02-04 | Nokia Corporation | Determination of event of interest |
US8265658B2 (en) | 2009-02-02 | 2012-09-11 | Waldeck Technology, Llc | System and method for automated location-based widgets |
US9397890B2 (en) | 2009-02-02 | 2016-07-19 | Waldeck Technology Llc | Serving a request for data from a historical record of anonymized user profile data in a mobile environment |
US9275151B2 (en) | 2009-02-06 | 2016-03-01 | Hewlett Packard Enterprise Development Lp | System and method for generating a user profile |
US8539359B2 (en) * | 2009-02-11 | 2013-09-17 | Jeffrey A. Rapaport | Social network driven indexing system for instantly clustering people with concurrent focus on same topic into on-topic chat rooms and/or for generating on-topic search results tailored to user preferences regarding topic |
US20120047087A1 (en) | 2009-03-25 | 2012-02-23 | Waldeck Technology Llc | Smart encounters |
US20120046995A1 (en) | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | Anonymous crowd comparison |
US8560608B2 (en) | 2009-11-06 | 2013-10-15 | Waldeck Technology, Llc | Crowd formation based on physical boundaries and other rules |
-
2010
- 2010-04-14 US US12/759,749 patent/US20120046995A1/en not_active Abandoned
- 2010-04-21 US US12/764,150 patent/US8554770B2/en not_active Expired - Fee Related
- 2010-04-21 US US12/764,148 patent/US20120047565A1/en not_active Abandoned
- 2010-04-21 US US12/764,143 patent/US20120046068A1/en not_active Abandoned
- 2010-04-28 US US12/769,031 patent/US20120047152A1/en not_active Abandoned
- 2010-04-28 US US12/768,973 patent/US20120046017A1/en not_active Abandoned
- 2010-04-29 US US12/769,802 patent/US20120047448A1/en not_active Abandoned
-
2013
- 2013-09-26 US US14/037,431 patent/US9053169B2/en not_active Expired - Fee Related
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6128412A (en) * | 1996-09-02 | 2000-10-03 | Fujitsu Limited | Statistical data compression/decompression method |
US20020083025A1 (en) * | 1998-12-18 | 2002-06-27 | Robarts James O. | Contextual responses based on automated learning techniques |
US20090013052A1 (en) * | 1998-12-18 | 2009-01-08 | Microsoft Corporation | Automated selection of appropriate information based on a computer user's context |
US20050227676A1 (en) * | 2000-07-27 | 2005-10-13 | Microsoft Corporation | Place specific buddy list services |
US7054614B1 (en) * | 2000-08-07 | 2006-05-30 | Denso Corporation | Context privacy for delivery of context-aware content for wireless terminals |
US20080005651A1 (en) * | 2001-08-13 | 2008-01-03 | Xerox Corporation | System for automatically generating queries |
US20030235173A1 (en) * | 2002-06-24 | 2003-12-25 | Intel Corporation | Call routing in a location-aware network |
US7424541B2 (en) * | 2004-02-09 | 2008-09-09 | Proxpro, Inc. | Method and computer system for matching mobile device users for business and social networking |
US20080082465A1 (en) * | 2006-09-28 | 2008-04-03 | Microsoft Corporation | Guardian angel |
US20090036102A1 (en) * | 2007-07-30 | 2009-02-05 | Sybase, Inc. | Context-Based Data Pre-Fetching and Notification for Mobile Applications |
US20100082512A1 (en) * | 2008-09-29 | 2010-04-01 | Microsoft Corporation | Analyzing data and providing recommendations |
US20130185750A1 (en) * | 2012-01-17 | 2013-07-18 | General Instrument Corporation | Context based correlative targeted advertising |
Cited By (32)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110093515A1 (en) * | 2009-10-15 | 2011-04-21 | Mary Elizabeth Albanese | Mobile local search platform |
US20160189272A1 (en) * | 2009-10-15 | 2016-06-30 | Binja, Inc. | Mobile local search platform |
US20130132566A1 (en) * | 2010-05-11 | 2013-05-23 | Nokia Corporation | Method and apparatus for determining user context |
US10277479B2 (en) * | 2010-05-11 | 2019-04-30 | Nokia Technologies Oy | Method and apparatus for determining user context |
US20120095979A1 (en) * | 2010-10-15 | 2012-04-19 | Microsoft Corporation | Providing information to users based on context |
US8818981B2 (en) * | 2010-10-15 | 2014-08-26 | Microsoft Corporation | Providing information to users based on context |
US20120102165A1 (en) * | 2010-10-21 | 2012-04-26 | International Business Machines Corporation | Crowdsourcing location based applications and structured data for location based applications |
US10169017B2 (en) * | 2010-10-21 | 2019-01-01 | International Business Machines Corporation | Crowdsourcing location based applications and structured data for location based applications |
US9848327B2 (en) | 2010-12-09 | 2017-12-19 | Inmarket Media Llc | Systems, apparatuses, and methods for secure beacon authentication via mobile devices |
US9883393B2 (en) | 2010-12-09 | 2018-01-30 | inMarkert Media LLC | Systems, apparatuses, and methods for secure beacon authentication via mobile devices |
US20130332410A1 (en) * | 2012-06-07 | 2013-12-12 | Sony Corporation | Information processing apparatus, electronic device, information processing method and program |
US10096041B2 (en) | 2012-07-31 | 2018-10-09 | The Spoken Thought, Inc. | Method of advertising to a targeted buyer |
US9420424B2 (en) | 2012-08-09 | 2016-08-16 | Tata Consultancy Services Limited | System and method for measuring the crowdedness of people at a place |
CN104488304A (en) * | 2012-08-09 | 2015-04-01 | 塔塔咨询服务有限公司 | A system and method for measuring the crowdedness of people at a place |
WO2014024209A1 (en) * | 2012-08-09 | 2014-02-13 | Tata Consultancy Services Limited | A system and method for measuring the crowdedness of people at a place |
US8984151B1 (en) * | 2013-02-05 | 2015-03-17 | Google Inc. | Content developer abuse detection |
US10649619B2 (en) * | 2013-02-21 | 2020-05-12 | Oath Inc. | System and method of using context in selecting a response to user device interaction |
US20140237425A1 (en) * | 2013-02-21 | 2014-08-21 | Yahoo! Inc. | System and method of using context in selecting a response to user device interaction |
US9980113B2 (en) * | 2014-12-29 | 2018-05-22 | Iridium Satellite Llc | Emergency communications from a local area network hotspot |
US20170127259A1 (en) * | 2014-12-29 | 2017-05-04 | Iridium Satellite Llc | Emergency communications from a local area network hotspot |
US10205696B2 (en) * | 2015-06-11 | 2019-02-12 | Avi Solomon | Systems methods circuits and associated computer executable code for facilitating selective messaging and multicasting |
WO2017040725A1 (en) * | 2015-08-31 | 2017-03-09 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US20190199661A1 (en) * | 2015-08-31 | 2019-06-27 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US10623349B2 (en) * | 2015-08-31 | 2020-04-14 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US10225217B2 (en) | 2015-08-31 | 2019-03-05 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US10972412B2 (en) | 2015-08-31 | 2021-04-06 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US11456980B2 (en) | 2015-08-31 | 2022-09-27 | Cordial Experience, Inc. | Systems and methods for distributed electronic communication and configuration |
US10346285B2 (en) | 2017-06-09 | 2019-07-09 | Microsoft Technology Licensing, Llc | Instrumentation of user actions in software applications |
US11263399B2 (en) * | 2017-07-31 | 2022-03-01 | Apple Inc. | Correcting input based on user context |
US20220366137A1 (en) * | 2017-07-31 | 2022-11-17 | Apple Inc. | Correcting input based on user context |
US11900057B2 (en) * | 2017-07-31 | 2024-02-13 | Apple Inc. | Correcting input based on user context |
WO2022132328A1 (en) * | 2020-12-14 | 2022-06-23 | Qualcomm Incorporated | Method of sub flow or activity classification |
Also Published As
Publication number | Publication date |
---|---|
US20120047152A1 (en) | 2012-02-23 |
US20120046995A1 (en) | 2012-02-23 |
US20120047184A1 (en) | 2012-02-23 |
US20140095516A1 (en) | 2014-04-03 |
US20120047565A1 (en) | 2012-02-23 |
US20120047448A1 (en) | 2012-02-23 |
US9053169B2 (en) | 2015-06-09 |
US8554770B2 (en) | 2013-10-08 |
US20120046017A1 (en) | 2012-02-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20120046068A1 (en) | Automatically performing user actions based on detected context-to-user-action correlations | |
US9473886B2 (en) | Systems and methods for associating communication information with a geographic location-aware contact entry | |
US8335473B2 (en) | Social interaction tracking | |
US9600141B2 (en) | Systems, apparatus, methods and computer-readable storage media facilitating information retrieval for a communication device | |
KR101382980B1 (en) | System and method of sharing information between wireless devices | |
CN108496317B (en) | Method and device for searching public resource set of residual key system information | |
US9654621B2 (en) | Methods and devices for prompting calling request | |
CN106714244B (en) | Wireless access method and device of terminal and terminal | |
US20170063758A1 (en) | Method, device, terminal, and router for sending message | |
CN104580637A (en) | Telephone number marking method, terminal and cloud server | |
CN105898573B (en) | Multimedia file playing method and device | |
CN107404723B (en) | Method and device for accessing base station | |
CN110896376B (en) | Message reminding method, message sending method, related device and equipment | |
EP2652966A1 (en) | A system and method for establishing a communication session between context aware portable communication devices | |
EP2991326B1 (en) | Method, apparatus and computer program product for processing communication identification | |
CN105939424B (en) | Application switching method and device | |
CN105101076B (en) | Information reminding method and device | |
US9706347B2 (en) | Method and device for determining position | |
CN106922005B (en) | Method and device for accessing wireless access point and computer readable storage medium | |
CN105634928A (en) | Social reminding method and device based on wearable device | |
CN107426401B (en) | Mute reminding method, device and terminal | |
CN104994211A (en) | Incoming call prompting method, device and system | |
CN110868495A (en) | Message display method and device | |
CN107889062B (en) | Offline positioning data learning method and device | |
CN108811080B (en) | Method, device and storage medium for cell registration |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: KOTA ENTERPRISES, LLC, DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KATPELLY, RAVI REDDY;KANDEKAR, KUNAL;CURTIS, SCOTT;SIGNING DATES FROM 20100416 TO 20100419;REEL/FRAME:024262/0483 |
|
AS | Assignment |
Owner name: WALDECK TECHNOLOGY, LLC, DELAWARE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:KOTA ENTERPRISES, LLC;REEL/FRAME:024859/0855 Effective date: 20100730 |
|
AS | Assignment |
Owner name: CONCERT DEBT, LLC, NEW HAMPSHIRE Free format text: SECURITY INTEREST;ASSIGNOR:WALDECK TECHNOLOGY, LLC;REEL/FRAME:036433/0382 Effective date: 20150801 Owner name: CONCERT DEBT, LLC, NEW HAMPSHIRE Free format text: SECURITY INTEREST;ASSIGNOR:WALDECK TECHNOLOGY, LLC;REEL/FRAME:036433/0313 Effective date: 20150501 |
|
AS | Assignment |
Owner name: CONCERT DEBT, LLC, NEW HAMPSHIRE Free format text: SECURITY INTEREST;ASSIGNOR:CONCERT TECHNOLOGY CORPORATION;REEL/FRAME:036515/0471 Effective date: 20150501 Owner name: CONCERT DEBT, LLC, NEW HAMPSHIRE Free format text: SECURITY INTEREST;ASSIGNOR:CONCERT TECHNOLOGY CORPORATION;REEL/FRAME:036515/0495 Effective date: 20150801 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |
|
AS | Assignment |
Owner name: CONCERT TECHNOLOGY CORPORATION, NEW HAMPSHIRE Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:WALDECK TECHNOLOGY, LLC;REEL/FRAME:051395/0425 Effective date: 20191203 |