Mining movement data to reveal interesting behavioral patterns has gained attention in recent years. One such pattern is the convoy pattern which consists of at least  m  objects moving together for at least  k  consecutive time instants where  m  and  k  are user-defined parameters. Existing algorithms for detecting convoy patterns, however do not scale to real-life dataset sizes. Therefore a distributed algorithm for convoy mining is inevitable. In this paper, we discuss the problem of convoy mining and analyze different data partitioning strategies to pave the way for a generic distributed convoy pattern mining algorithm.
['Faisal Orakzai', 'Thomas Devogele', 'Toon Calders']
Towards distributed convoy pattern mining