Abstract: One or more computing devices, systems, and/or methods for future event recommendation are provided. For example, messages of a user account of a user are parsed to identify messages corresponding to events attended by the user. Event features are extracted from the messages, where an event feature is descriptive of an aspect of an event. An event database of future events is queried using the event features to identify future events having one or more of the event features. A description of the future events is constructed and provided to the user.

Abstract: One or more computing devices, systems, and/or methods for future event recommendation are provided. For example, messages of a user account of a user are parsed to identify messages corresponding to events attended by the user. Event features are extracted from the messages, where an event feature is descriptive of an aspect of an event. An event database of future events is queried using the event features to identify future events having one or more of the event features. A description of the future events is constructed and provided to the user.

Abstract: One or more computing devices, systems, and/or methods for graphically presenting messages are provided. For example, a plurality of messages, associated with a messaging account, comprising a first message and a second message may be received. A first graphical object may be generated by a device, such as a server and/or a client device of a user, based upon the first message. A second graphical object may be generated by the device based upon the second message. In response to receiving a request to access the messaging account, the device may present the first graphical object. In response to receiving one or more user inputs corresponding to the first graphical object, an action may be performed and/or the second graphical object may be presented.

Abstract: Methods and systems for predicting content consumption are provided herein. An application log of a user, comprising a user's application data, and a viewing log of the user, comprising the user's viewing data (e.g., television programs watched by the user), may be evaluated over a time period to construct a model. The model may comprise a correlation between the viewing log and the application log during the time period (e.g., what applications the user interacts with while watching a program). Second application data, regarding application usage of a second user, may be extracted. The model may be applied to the second application data to identify an expected viewing action of the second user (e.g., what program the second user is likely to watch during the time period based upon applications used by the second user). The second user may be provided with content related to the expected viewing action.

Abstract: One or more computing devices, systems, and/or methods for future event recommendation are provided. For example, messages of a user account of a user are parsed to identify messages corresponding to events attended by the user. Event features are extracted from the messages, where an event feature is descriptive of an aspect of an event. An event database of future events is queried using the event features to identify future events having one or more of the event features. A description of the future events is constructed and provided to the user.

Abstract: One or more systems and/or methods for determining a query date range and/or searching a content corpus are provided. A set of content items (e.g., digital images, videos, etc.), associated with an event, may be identified from a content corpus. The set of content items may be evaluated to identify temporal features (e.g., digital time stamps) for the set of content items. A query date range for the event may be determined based upon the temporal features (e.g., users may capture photos that are related to Christmas from December 4th to December 27th). In an example, responsive to receiving a search query, associated with the event, the search query may be adjusted based upon the query date range to create an adjusted search query. The content corpus may be searched using the adjusted search query to create search query results for the search query.

Abstract: One or more computing devices, systems, and/or methods for graphically presenting messages are provided. For example, a plurality of messages, associated with a messaging account, comprising a first message and a second message may be received. A first graphical object may be generated by a device, such as a server and/or a client device of a user, based upon the first message. A second graphical object may be generated by the device based upon the second message. In response to receiving a request to access the messaging account, the device may present the first graphical object. In response to receiving one or more user inputs corresponding to the first graphical object, an action may be performed and/or the second graphical object may be presented.

Abstract: One or more systems and/or methods for determining a query date range and/or searching a content corpus are provided. A set of content items (e.g., digital images, videos, etc.), associated with an event, may be identified from a content corpus. The set of content items may be evaluated to identify temporal features (e.g., digital time stamps) for the set of content items. A query date range for the event may be determined based upon the temporal features (e.g., users may capture photos that are related to Christmas from December 4th to December 27th). In an example, responsive to receiving a search query, associated with the event, the search query may be adjusted based upon the query date range to create an adjusted search query. The content corpus may be searched using the adjusted search query to create search query results for the search query.

Abstract: Methods and systems for predicting content consumption are provided herein. An application log of a user, comprising a user's application data, and a viewing log of the user, comprising the user's viewing data (e.g., television programs watched by the user), may be evaluated over a time period to construct a model. The model may comprise a correlation between the viewing log and the application log during the time period (e.g., what applications the user interacts with while watching a program). Second application data, regarding application usage of a second user, may be extracted. The model may be applied to the second application data to identify an expected viewing action of the second user (e.g., what program the second user is likely to watch during the time period based upon applications used by the second user). The second user may be provided with content related to the expected viewing action.