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Clue-based Spatio-textual Query

Summary: Introduces clue-based POI retrieval, matching partial, approximate spatial relationships among nearby places rather than names or addresses. A quality-tolerant context similarity, cross-valuation ensemble, and roll-out-star R-tree enable accurate, efficient top-k search. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11737
Venue
VLDB
Year
2017
Pagerank
5.9425753e-05
Overall Rank
6,217 | 57.35%
DOI
10.14778/3055540.3055545

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{liu_vldb17,
        title = {{Clue-based Spatio-textual Query}},
        author = {Liu, Junling and Deng, Ke and Sun, Huanliang and Ge, Yu and Zhou, Xiaofang and Jensen, Christian S.},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {5},
        pages = {529--540},
        doi = {10.14778/3055540.3055545},
        url = {https://doi.org/10.14778/3055540.3055545},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
11,578 Example-based Spatial Pattern Matching 2022 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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

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