User interaction pattern extraction for device personalization

摘要

A context-aware personalization system operable with a device such as a smartphone, tablet, personal computer (PC), game console, etc. extracts user interaction patterns from a graph, which is generated using telemetry data points, of a device user's behaviors and interactions. The telemetry data is mined from instrumented applications, operating system, and other components executing on the device. A machine learning pattern recognition algorithm is applied to the behavior and interaction graph to generate a dataset that can include a prioritized list of activities. The list is used to automatically implement personalization of the local device that are tailored to the user while also enabling background agents and processes associated with lower priority applications to be suspended to preserve device resources such as processor cycles, memory, battery power, etc. and increase device performance.

主权项

1. A device, comprising:
one or more processors; a user interface (UI) for interacting with a user of the device; and a memory device storing code associated with one or more applications and computer-readable instructions which, when executed by the one or more processors, perform a method comprising the steps of:
collecting telemetry data from the one or more applications, the telemetry data at least describing user interactions with the one or more applications,obtaining a prioritized list of activities that are associated with the one or more applications, the prioritized list being generated by application of a pattern recognition methodology to extract user interaction patterns from the telemetry data,personalizing the device responsively to a prioritized list of activities, andsuspending operations of an application associated with activities in the list having a priority below a predetermined threshold.