Exploring Human Movement Behaviour Based on Mobility Association Rule Mining of Trajectory Traces

Abstract

With the emergence of location sensing technologies there is a growing interest to explore spatio-temporal GPS (Global Positioning System) traces collected from various moving agents (ex: mobile-users, GPS-equipped vehicles etc.) to facilitate location-aware applications. This paper, therefore focuses on finding meaningful patterns from spatio-temporal data (GPS log) of human movement history and measures the interestingness of the extracted patterns. An experimental evaluation on GPS data-set of an academic campus demonstrates the efficacy of the system and its potential to extract meaningful rules from real-life dataset.