Abstract

A system and method are disclosed that trigger a smart response to a button action when two or more running applications have applicable actions on a mobile device. The system includes a machine learning algorithm (MLA) built into the operating system that analyzes and learns from user actions. When the system detects a hardware button press, it retrieves possible actions/events that may be triggered for the current app and other running apps and processes. The actions are evaluated by computing a combination of scores involving machine-learned, rule-based scores provided by the apps and real-time signals such as location, time, user activity, etc. The system then triggers an action that has the highest score surpassing a predetermined threshold. The disclosed method would provide improved user experience, and also new, useful button actions that previously were not available to the user.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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