Swarm: Mining Relaxed Temporal Moving Object Clusters

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Executive Summary

Recent improvements in positioning technology make massive moving object data widely available. One important analysis is to find the moving objects that travel together. Existing methods put a strong constraint in defining moving object cluster, that they require the moving objects to stick together for consecutive timestamps. The key observation is that the moving objects in a cluster may actually diverge temporarily and congregate at certain timestamps. Motivated by this, the authors propose the concept of swarm which captures the moving objects that move within arbitrary shape of clusters for certain timestamps that are possibly nonconsecutive. The goal of the paper is to find all discriminative swarms, namely closed swarm.

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