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BT-Tree: A Reinforcement Learning Based Index for Big Trajectory Data

Summary: BT-Tree: a reinforcement-learning–driven index for big trajectory data, built by recursive bi-partitioning to accelerate range and KNN queries. It combines a cost-function-based build (CFBM) that encodes data and workload, with an RL refinement to avoid locally optimal cuts; experiments with up to 800M points show CFBM outperforms baselines, and RL consistently wins, especially on large datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h4a0157f59405157e
Venue
SIGMOD
Year
2024
Pagerank
5.0954911e-05
Overall Rank
10,007 | 32.75%
DOI
10.1145/3677130

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{gu_sigmod24,
        title = {{BT-Tree: A Reinforcement Learning Based Index for Big Trajectory Data}},
        author = {Gu, Tu and Feng, Kaiyu and Yang, Jingyi and Cong, Gao and Long, Cheng and Zhang, Rui},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3677130},
        url = {https://dl.acm.org/doi/10.1145/3677130},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,854 Rethinking Learned Index and LSM-tree Integration 2026 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 25 of 25 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 0.0019923528
4 The R*-tree: An Efficient and Robust Access Method for Points and Rectangles 1990 SIGMOD 0.0011402175
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046363107
574 Indexing the Positions of Continuously Moving Objects 2000 SIGMOD 0.00016165512
869 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013363241
985 The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries 2003 VLDB 0.00012679233
1,128 Qd-tree: Learning Data Layouts for Big Data Analytics 2020 SIGMOD 0.00011901941
1,188 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011598149
1,228 Fractals for Secondary Key Retrieval 1989 PODS 0.00011427053
1,440 LISA: A Learned Index Structure for Spatial Data 2020 SIGMOD 0.00010638444
1,877 Effectively Learning Spatial Indices 2020 VLDB 9.4498401e-05
2,023 Distributed Trajectory Similarity Search 2017 VLDB 9.167612e-05
2,198 DITA: Distributed In-Memory Trajectory Analytics 2018 SIGMOD 8.8738834e-05
2,313 The MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries 2001 VLDB 8.6585352e-05
2,422 Novel Approaches to the Indexing of Moving Object Trajectories 2000 VLDB 8.4857212e-05
2,912 Indexing Large Trajectory Data Sets With SETI* 2003 CIDR 7.8683521e-05
3,162 Effective Travel Time Estimation: When Historical Trajectories over Road Networks Matter 2020 SIGMOD 7.5760668e-05
4,135 ST2B-tree: A Self-Tunable Spatio-Temporal B+-tree Index for Moving Objects 2008 SIGMOD 6.7843671e-05
4,851 The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data 2023 SIGMOD 6.377837e-05
5,745 VRE: A Versatile, Robust, and Economical Trajectory Data System 2022 VLDB 6.0070567e-05
6,598 PPQ-Trajectory: Spatio-temporal Quantization for Querying in Large Trajectory Repositories 2021 VLDB 5.7383366e-05
7,306 Theoretically Optimal and Empirically Efficient R-trees with Strong Parallelizability 2018 VLDB 5.5571749e-05
8,186 Towards Designing and Learning Piecewise Space-Filling Curves 2023 VLDB 5.3800965e-05
9,436 Boosting Moving Object Indexing through Velocity Partitioning 2012 VLDB 5.1763176e-05
10,172 PLATON: Top-down R-tree Packing with Learned Partition Policy 2023 SIGMOD 5.0658661e-05
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