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Trajectory Simplification: An Experimental Study and Quality Analysis

Summary: Comprehensive benchmark of 25 trajectory-simplification algorithms across five datasets with diverse motion patterns. Goes beyond error metrics to assess reduced trajectories’ utility for spatio-temporal queries, deriving practical algorithm-selection guidance. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hbe6a98e2ab4d64e9
Venue
VLDB
Year
2018
Pagerank
7.7578378e-05
Overall Rank
3,009 | 79.78%
DOI
10.14778/3213880.3213885

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb18,
        title = {{Trajectory Simplification: An Experimental Study and Quality Analysis}},
        author = {Zhang, Dongxiang and Ding, Mengting and Yang, Dingyu and Liu, Yi and Fan, Ju and Shen, Heng Tao},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {9},
        pages = {934--946},
        doi = {10.14778/3213880.3213885},
        url = {https://doi.org/10.14778/3213880.3213885},
        year = {2018}
}

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