Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning
Summary: Addresses SimSub: finding subtrajectories most similar to a query trajectory. Proposes exact and approximate algorithms; two DRL-based approaches beat non-learning baselines in effectiveness and efficiency, with experiments on real-world trajectory datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zheng Wang
- 2. Cheng Long
- 3. Gao Cong
- 4. Yiding Liu
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,572 | The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data | 2023 | SIGMOD | 5.4277273e-05 |
| 7,021 | VRE: A Versatile, Robust, and Economical Trajectory Data System | 2022 | VLDB | 4.8581131e-05 |
| 11,242 | Effective and Efficient Route Planning Using Historical Trajectories on Road Networks | 2023 | VLDB | 4.1945683e-05 |
| 11,257 | Efficient Non-Learning Similar Subtrajectory Search | 2023 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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