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PRESS: A Novel Framework of Trajectory Compression in Road Networks

Summary: PRESS separates road-network trajectory geometry from temporal information, combining Hybrid Spatial Compression with error-bounded Temporal Compression. Its compressed representation supports spatiotemporal queries without full decompression, achieving greater storage savings under bounded error. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11131
Venue
VLDB
Year
2014
Pagerank
7.6626865e-05
Overall Rank
3,179 | 78.20%
DOI
10.14778/2732939.2732940

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{song_vldb14,
        title = {{PRESS: A Novel Framework of Trajectory Compression in Road Networks}},
        author = {Song, Renchu and Sun, Weiwei and Zheng, Baihua and Zheng, Yu},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {9},
        pages = {661--672},
        doi = {10.14778/2732939.2732940},
        url = {https://doi.org/10.14778/2732939.2732940},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,193 On Map-Matching Vehicle Tracking Data 2005 VLDB 0.00011730808
1,381 Finding Time Period-Based Most Frequent Path in Big Trajectory Data 2013 SIGMOD 0.00010965263
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