Trajectory similarity join in spatial networks

摘要: The matching of similar pairs objects, called similarity join, is fundamental functionality in data management. We consider the case trajectory join (TS-Join), where objects are trajectories vehicles moving road networks. Thus, given two sets and a threshold θ, TS-Join returns all from with above θ. This targets applications such as near-duplicate detection, cleaning, ridesharing recommendation, traffic congestion prediction.With these mind, we provide purposeful definition similarity. To enable efficient processing on large trajectories, develop search space pruning techniques take into account parallel capabilities modern processors. Specifically, present two-phase divide-and-conquer algorithm. For each trajectory, algorithm first finds trajectories. Then it merges results to achieve final result. exploits an upper bound spatiotemporal heuristic scheduling strategy for pruning. algorithm's per-trajectory searches independent other can be performed parallel, merging has constant cost. An empirical study real offers insight performance demonstrates that capable outperforming well-designed baseline by order magnitude.