Discovery of Collocation Episodes in Spatiotemporal Data

Huiping Cao, Nikos Mamoulis, David Cheung
2006 IEEE International Conference on Data Mining. Proceedings  
Given a collection of trajectories of moving objects with different types (e.g., pumas, deers, vultures, etc.), we introduce the problem of discovering collocation episodes in them (e.g., if a puma is moving near a deer, then a vulture is also going to move close to the same deer with high probability within the next 3 minutes). Collocation episodes catch the inter-movement regularities among different types of objects. We formally define the problem of mining collocation episodes and propose
more » ... o scaleable algorithms for its efficient solution. We empirically evaluate the performance of the proposed methods using synthetically generated data that emulate real-world object movements.
doi:10.1109/icdm.2006.59 dblp:conf/icdm/CaoMC06 fatcat:lbjyfmua2verriemanzonxc5w4