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A General and Parallel Platform for Mining Co-Movement Patterns over Large-scale Trajectories

Summary: Unifies prior co-movement definitions into a general pattern class for large-scale trajectories. Presents two parallel Spark-based frameworks for scalable mining, and demonstrates effectiveness on real datasets with hundreds of millions of points. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11529
Venue
VLDB
Year
2017
Pagerank
6.0416152e-05
Overall Rank
4,622 | 67.85%
DOI
-

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Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
36 Fast Algorithms for Mining Association Rules 1994 VLDB 0.00076161096
1,334 SkewTune: Mitigating Skew in MapReduce Applications 2012 SIGMOD 0.0001250413
1,718 Swarm: Mining Relaxed Temporal Moving Object Clusters 2010 VLDB 0.00010789285
1,745 Discovery of Convoys in Trajectory Databases 2008 VLDB 0.00010702338
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