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: Personalized notifications are provided to a user. The notifications correspond to events, which can include information items, unaddressed or unnoticed by a user. The unaddressed events may be determined based on sensor data provided by a user device associated with the user including user activity pattern information. Further, an urgency level of the unaddressed event and user availability for responding to the event may be determined The availably may comprise a model with score(s) corresponding to the user's capability for carrying out tasks associated with addressing the event. Additionally, notification content may be generated based on information about availability and the unaddressed event, and used to provide notification(s). The notification content may include a recommendation to present a notification to the user at a time determined likely to be convenient for the user to be notified of the event or where the user likely has capacity to address the event appropriately.

Abstract: Personalized reminder notifications are provided regarding communication-related events. The reminders correspond to missed communications or events that are unaddressed by a user, and may be determined based on sensor data provided by a user device. Further, an urgency level for the unaddressed event and a user availability model for responding to the event also may be determined. The model may include a set of scores corresponding to the user's capability for carrying out tasks associated with responding to the unaddressed event, such as composing email or initiating a call. Additionally, reminder notification content may be generated based on information about availability and the unaddressed event, and used to provide notification(s). The notification content may include a recommendation to present a notification to the user at a future time determined likely to be convenient for the user to respond to the event or where the user likely will have capacity to respond appropriately.

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: Data mining techniques are described. In an implementation, one or more segments are extracted from a multivariate distribution, each of the segments describing intra-dependencies of a set of input variables. A list is output in a user interface referencing each of the one or more segments and a respective score indicating how interesting the segment is with respect to variable dependencies. In another implementation, a change is made to an observed distribution of data and an effect is calculated of the change. The change with the most desirable effect is chosen, the process being repeated until no more significant changes can be made or the overall change exceeds a limit.

Abstract: Data mining techniques are described. In an implementation, one or more computer-readable media include instructions that are executable on a device to output a user interface describing a list of segments ranked according to a ranking function, the segments demonstrating distinct behavior in one or more attributes over a plurality of clients described in client data and the ranking function containing settings that are enterable via the user interface to specify a business agenda.