Abstract: In implementations, a divergence from a pattern of detected instances of an event is identified, where the event is of a routine of a user. The identified divergence corresponds to an out of routine event. Contextual information is generated corresponding to the identified out of routine event. Furthermore, one or more recommended actions for presenting content to the user are selected based on the contextual information. An indication of the identified out of routine event, the contextual information, and the one or more recommended actions are provided to a service, which may be an application on a user device. The service can present content to the user based on the identified out of routine event, the generated contextual information corresponding to the identified out of routine event, and the selected one or more recommended actions. The service may follow or disregard any of the selected one or more recommended actions.

Abstract: An electronic calendaring system provides contextual calendar conflict resolution by dynamically evaluating the contexts of a user's obligations and offering the user assistance in scheduling non-conflicting events in a calendar. The electronic calendaring system generates one or more electronic calendar conflict resolution options based on contextual information associated with conflicting calendar events. An event conflict evaluator identifies a calendar conflict between at least two calendar events within received calendar event information. An event context evaluator collects contextual information about the conflicting calendar events. A conflict resolution mediator ranks available time slots to which at least one of the conflicting calendar events can be rescheduled based on the collected contextual information. The conflict resolution mediator further communicates a conflict resolution option message via a user interface of a computing device.

Abstract: In implementations, a divergence from a pattern of detected instances of an event is identified, where the event is of a routine of a user. The identified divergence corresponds to an out of routine event. Contextual information is generated corresponding to the identified out of routine event. Furthermore, one or more recommended actions for presenting content to the user are selected based on the contextual information. An indication of the identified out of routine event, the contextual information, and the one or more recommended actions are provided to a service, which may be an application on a user device. The service can present content to the user based on the identified out of routine event, the generated contextual information corresponding to the identified out of routine event, and the selected one or more recommended actions. The service may follow or disregard any of the selected one or more recommended actions.

Abstract: Architecture that enables the discovery of relevant applications, where the relevance is personalized to the user and user interests. New, relevant, and interesting applications are personalized to the user based on friends and/or people with whom the user shares common interests (e.g., social networks), based on queries for a popular application within a geographical area, and/or collaborative filtering. Moreover, users who employ the disclosed architecture can maintain anonymity to prevent the exposure of personal identifying details. Social-based application discovery, location-based application discovery, anonymous-profile-based application discovery, and collaborative-filtering-based application discovery, are provided. Application installs, uninstalls, and frequency of user interaction are also available, as well as privacy modes for privacy protection.

Abstract: Messages to a focal user are organized by relevance of the message originators. A visual representation of the messages includes a focal user representation (textual or graphic) and multiple contact representations (textual or graphic). The contact representations are displayed at respective relevance distances from the focal user representation. Text regions present the contents of messages from the source contacts, e.g., using graphic novel-style word balloons. The contact representations can be positioned on screen in maps, radar format, or other configurations. Users can filter contacts according to relevance, and can filter messages by pertinence.

Abstract: Architecture that creates a multi-dimensional spatial model of a mobile device based on data obtained from sensors, such as associated with the mobile device, for example. The spatial model defines the location of the mobile device in space, as well as the device orientation (e.g., heading, and tilt). The spatial model is used to determine a target location (or point) in space at which the mobile device is aiming. The spatial model can be generated based on sensing subsystems that include, but are not limited to, geolocation subsystem (e.g., GPS-global positioning system), a directional (or heading) sensor such as a compass, and gyroscope information to calculate the device tilt relative to the target location.

Abstract: Architecture that motivates and utilizes users as the means for capturing geographical data of a desired location. The architecture incentivizes users (e.g., large numbers of mobile-phone and mobile-computer users) to provide the data in the form of geolocation information trails and images captured by user devices. Thus, users take multiple pictures, for example, and can validate existing coverage of specific points of interest based on variable needs of the requestor. One motivational technique is by using augmented reality (AR) games, which include shooting targets associated with the point of interest (e.g., a street). Thus, the game can be designed for the data accumulation, which includes visual data. Additionally, the architecture can determine the areas or points of interest for validation and/or additional coverage by comparing live video data to an image database to decide of the need for update.

Abstract: Architecture that motivates and utilizes users as the means for capturing geographical data of a desired location. The architecture incentivizes users (e.g., large numbers of mobile-phone and mobile-computer users) to provide the data in the form of geolocation information trails and images captured by user devices. Thus, users take multiple pictures, for example, and can validate existing coverage of specific points of interest based on variable needs of the requestor. One motivational technique is by using augmented reality (AR) games, which include shooting targets associated with the point of interest (e.g., a street). Thus, the game can be designed for the data accumulation, which includes visual data. Additionally, the architecture can determine the areas or points of interest for validation and/or additional coverage by comparing live video data to an image database to decide of the need for update.

Abstract: Architecture that enables communication of a message from a requesting (sending) user to a single target user and/or group of target users based on current geographic location of the target user(s) while hiding the identities of the requesting user and the target user(s). This anonymity capability is provided by mediating messages between the users (requesting and target) via an anonymous messaging component (e.g., a service) that maintains anonymity of the users relative to one another. The anonymous messaging component does not publish user identities, since the component mediates between the sender and the receiver(s).

Abstract: Information is automatically located which is relevant to source content that a user is viewing on a user interface without requiring the user to perform an additional search or navigate links of the source content. The source content can be, e.g., a web page or a document from a word processing or email application. The relevant information can include images, videos, web pages, maps or other location-based information, people-based information and special services which aggregate different types of information. Related content is located by analyzing textual content, user behavior and connectivity relative to the source. The related content is scored for similarity to the source. Content which is sufficiently similar but not too similar is selected. Similar related content is grouped to select representative results. The selected content is filtering in multiple stages based on attribute priorities to avoid unnecessary processing of content which is filtered out an early stage.

Abstract: A particular method of content personalization based on user information includes receiving data representing an information retrieval task. The data is received at a server from a computing device associated with a user. The information retrieval task is executed to generate result information. Personalization information associated with the user that is relevant to the information retrieval task is retrieved. The personalization information associated with the user includes information associated with at least one of a genotype of the user and a phenotype of the user. The method includes modifying the result information based on the retrieved personalization information to generate personalized result information.

Abstract: Messages to a focal user are organized by relevance of the message originators. A visual representation of the messages includes a focal user representation (textual or graphic) and multiple contact representations (textual or graphic). The contact representations are displayed at respective relevance distances from the focal user representation. Text regions present the contents of messages from the source contacts, e.g., using graphic novel-style word balloons. The contact representations can be positioned on screen in maps, radar format, or other configurations. Users can filter contacts according to relevance, and can filter messages by pertinence.

Abstract: Information is automatically located which is relevant to source content that a user is viewing on a user interface without requiring the user to perform an additional search or navigate links of the source content. The source content can be, e.g., a web page or a document from a word processing or email application. The relevant information can include images, videos, web pages, maps or other location-based information, people-based information and special services which aggregate different types of information. Related content is located by analyzing textual content, user behavior and connectivity relative to the source. The related content is scored for similarity to the source. Content which is sufficiently similar but not too similar is selected. Similar related content is grouped to select representative results. The selected content is filtering in multiple stages based on attribute priorities to avoid unnecessary processing of content which is filtered out an early stage.