Evidence-based behavioral model for calendar schedules of individual mobile phone users

The electronic calendar usually serves as a personal organizer and is a valuable resource for managing daily activities or schedules of the users. Naturally, a calendar provides various contextual information about individual's scheduled events/appointments, e.g., meeting. A number of researchers have utilized such information to predict human behavior for mobile communication, by assuming a predefined event-behavior mapping which is static and non-personalized. However, in the real world, people differ from each other in how they respond to incoming calls during their scheduled events, even a particular individual may respond differently subject to what type of event is scheduled in the calendar. Thus a static behavioral model does not necessarily map to calendar schedules and corresponding phone call response behavior of individuals. Therefore, we propose an evidence based behavioral model (EBM) that dynamically identifies the actual call response behavior of individuals for various calendar events based on their mobile phone log that records the data related to a user's phone call activities. Experiments on real datasets show that our proposed technique better captures the user's call response behavior for various calendar events, thereby enabling more appropriate rules to be created for the purpose of automated handling of incoming calls in an intelligent call interruption management system.