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Swarm: Mining Relaxed Temporal Moving Object Clusters

Summary: Defines swarms: moving objects clustering in arbitrary shapes at non-consecutive timestamps, relaxing contiguity. Introduces ObjectGrowth with pruning and on-the-fly closure to enumerate all closed swarms efficiently; validated on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10121
Venue
VLDB
Year
2010
Pagerank
0.00010814313
Overall Rank
1,704 | 88.16%
DOI
-

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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 0.00076114894
251 Robust and Fast Similarity Search for Moving Object Trajectories 2005 SIGMOD 0.00030589775
358 On The Marriage of Lp-norms and Edit Distance 2004 VLDB 0.00026059337
1,127 Trajectory Clustering: A Partition-and-Group Framework 2007 SIGMOD 0.00013801775
1,741 Discovery of Convoys in Trajectory Databases 2008 VLDB 0.00010696301
8,413 MoveMine: Mining Moving Object Databases 2010 SIGMOD 4.5137116e-05
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