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Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories

Summary: Flink-based framework for real-time, distributed co-movement detection on unbounded trajectory streams. Two-layer-indexed range joins accelerate clustering, while FBA/VBA partitioning, bit compression, and candidate enumeration reduce pattern search from exponential to linear. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12006
Venue
VLDB
Year
2019
Pagerank
5.7470112e-05
Overall Rank
6,880 | 52.80%
DOI
10.14778/3339490.3339502

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{chen_vldb19,
        title = {{Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories}},
        author = {Chen, Lu and Gao, Yunjun and Fang, Ziquan and Miao, Xiaoye and Jensen, Christian S. and Guo, Chenjuan},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {10},
        pages = {1208--1220},
        doi = {10.14778/3339490.3339502},
        url = {https://doi.org/10.14778/3339490.3339502},
        year = {2019}
}

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