Efficient Mining of Regional Movement Patterns in Semantic Trajectories
Summary: Proposes RegMiner, a density-based regional semantic trajectory miner that finds locally dense sequential patterns, not global ones. Uses a spatial density metric to quantify regional frequency, enabling fast mining and revealing local patterns with speedups over global methods. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Dong-Wan Choi
- 2. Jian Pei
- 3. Thomas Heinis
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Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0032169493 |
| 1,115 | Finding Time Period-Based Most Frequent Path in Big Trajectory Data | 2013 | SIGMOD | 0.00013894562 |
| 1,126 | Trajectory Clustering: A Partition-and-Group Framework | 2007 | SIGMOD | 0.00013821443 |
| 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 |
| 8,302 | Splitter: Mining Fine-Grained Sequential Patterns in Semantic Trajectories | 2014 | VLDB | 4.5435639e-05 |
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