ADAPTIVE TASK COMMUNICATION BASED ON AUTOMATED LEARNING AND CONTEXTUAL ANALYSIS OF USER ACTIVITY

摘要

The techniques disclosed herein improve existing systems by automatically identifying tasks from a number of different types of user activity and providing suggestions for the tasks to one or more selected delivery mechanisms. A system compiles the tasks and pushes each task to a personalized task list of a user. The delivery of each task may be based on any suitable user activity, which may include communication between one or more users or a user's interaction with a particular file or a system. The system can identify timelines, performance parameters, and other related contextual data associated with the task. The system can identify a delivery schedule for the task to optimize the effectiveness of the delivery of the task. The system can also provide smart notifications. When a task conflicts with a person's calendar, the system can resolve scheduling conflicts based on priorities of a calendar event.