Predicting how you respond to phone calls: towards discovering temporal behavioral rules

Abstract

Discovering temporal rules that capture an individual's phone call response behavior is essential to building intelligent individualized call interruption management system. The key challenge to discovering such temporal rules is identifying within a phone call log the time boundaries that delineate periods when an individual user rejects or accepts phone calls. Moreover, potential data sparsity in phone call logs imposes additional challenge in discovering applicable rules. In this paper, we address the above issues and present a hybrid approach to identify the effective time boundaries for discovering temporal behavioral rules of individual mobile phone users utilizing calendar and mobile phone data. Our preliminary experiments on real datasets show that our proposed hybrid approach dynamically identifies better time boundaries based on like behavioral patterns and outperforms the existing calendar-based approach (CBA) and log-based approach (LBA) to discovering the temporal behavior rules of individual mobile phone users.