A user activity pattern may be ascertained using signal data from a set of computing devices. The activity pattern may be used to infer user intent with regards to a user interaction with a computing device or to predict a likely future action by the user. In one implementation, a set of computing devices is monitored to detect user activities using sensors associated with the computing devices. Activity features associated with the detected user activities are determined and used to identify an activity pattern based on a plurality of user activities having similar features. Examples of user activity patterns may include patterns based on time, location, content, or other context. The inferred user intent or predicted future actions may be used to provide improved user experiences, such as personalization, modifying functionality of user devices, or providing more efficient consumption of bandwidth or power.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computerized system comprising: one or more sensors configured to provide sensor data; a user activity monitor configured to identify and monitor a user device and user activity associated with the user device; an activity pattern inference engine configured to determine an activity pattern from a plurality of activity events; one or more processors; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, implement a method of inferring a user activity pattern, the method comprising: a) identifying a set of user devices associated with a user; b) monitoring, using the user activity monitor, the set of user devices to detect a user activity event; c) upon detecting a user activity event, determining a set of activity features associated with the activity event, the set of activity features determined based at least in part on the sensor data; d) storing a record of the activity event and associated activity features in an activity event data store that comprises records of a plurality of activity events; e) using the activity pattern inference engine to identify an activity pattern based on an analysis of the plurality of activity events to determine a set of activity events having similar activity features; and f) storing a description of the activity pattern in an activity pattern data store. 2. The computerized system of claim 1, wherein monitoring the set of user devices comprises analyzing user data corresponding to user devices to detect an indication of a user activity event, and wherein the user data corresponding to user devices is provided at least in part by the one or more sensors. 3. The computerized system of claim 1, wherein the sensor data comprises one or more of location-related data, time-related data, usage-related data, or data about the user. 4. The computerized system of claim 1, wherein the activity event comprises one or more of browsing to a website, launching an application, initiating a communication, performing a search query, setting a reminder, or scheduling an event on a calendar. 5. The computerized system of claim 1, wherein the set of user devices comprises a single user device. 6. The computerized system of claim 1, further comprising determining contextual information associated with the detected activity event, wherein a subset of the set of activity features associated with the activity event are further determined based in part on the contextual information. 7. The computerized system of claim 6, wherein at least a portion of the contextual information is determined using a semantic analysis of features associated with the activity event. 8. The computerized system of claim 1, wherein the set of associated activity features comprise one or more features related to content associated with the activity event (a content feature), date or time of the activity event (date-time feature), location of the activity event (location feature), device-usage related features associated with the activity event (device-usage feature), or contextual information associated with the activity event. 9. The computerized system of claim 1, wherein activity features are determined to be similar based on a comparison of the same category of activity features using a similarity threshold that is predetermined according to the category of the compared activity features. 10. The computerized system of claim 9, wherein the same category of activity features comprises one of a content feature, date-time feature, location feature, or device-usage feature. 11. The computerized system of claim 1, further comprising determining a confidence score associated with the identified activity pattern, based on the number of activity events used to identify the pattern, the confidence score indicating a probability that the user will behave according to the activity pattern. 12. The computerized system of claim 1, further comprising providing an enhanced user experience to the user based on the identified activity pattern. 13. A computerized system comprising: one or more sensors configured to provide sensor data, each sensor associated with a user device in a set of user devices associated with a user; one or more processors; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, implement a method of inferring a probable future user action, the method comprising: a) accessing an inferred user activity pattern for a user; b) predicting a probable future activity event based on the activity pattern and a context determined at least in part from the sensor data; and c) providing, using at least one user device in the set of user devices, an enhanced user experience based on the determined probable future activity event. 14. The computerized system of claim 13, wherein the sensor data for predicting a probable future activity event is provided from a sensor associated with a first user device in the set of user devices, and the enhanced user experience is provided using a second user device in the set of user devices. 15. The computerized system of claim 13, wherein the provided enhanced user experience comprises one of a recommendation, notification, request, or suggestion related to the probable future activity. 16. The computerized system of claim 13, wherein the provided enhanced user experience comprises automatically carrying out the probable future activity at a time or location consistent with the inferred user activity pattern. 17. The computerized system of claim 13, wherein the predicted probable future activity event comprises connecting, at a future time, a user device having a battery to a power source to charge the battery, and wherein the enhanced user experience comprises a battery power management service that reduces power consumption by the user device based on the future time. 18. The computerized system of claim 13, wherein the predicted probable future activity event comprises a sequence of user actions. 19. A computerized method of providing an enhanced user experience using one or more computing devices associated with a user, the method comprising: identifying a set of computing devices associated with the user, at least a subset of the set of computing devices having one or more sensors configured to provide sensor data; determining an activity pattern of user activity associated with a first computing device in the set of computing devices by: (a) monitoring, using a user activity monitor, the set of computing devices to detect a plurality of user activity events; (b) upon detecting each user activity event, determining a set of activity features associated with the activity event, the set of activity features determined based at least in part on sensor data from at least a first computing device in the subset of computing devices having one or more sensors; (c) determining an activity pattern based on an analysis of the plurality of user activity events to determine a set of activity events having similar activity features; predicting a probable future activity event based on the determined activity pattern and a context determined at least in part from the sensor data; determining a confidence score associated with the predicted probable future activity event based at least in part on the number of user activity events used to determine the pattern, the confidence score indicating a probability that the future activity event will occur; and providing, using at least one computing device in the set of computing devices, an enhanced user experience based on the determined probable future activity event and corresponding confidence score. 20. The computerized method of claim 19, wherein the enhanced user experience is provided using a second computing device in the set of computing devices that is different than the first computing device.