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Processing and Optimizing Main Memory Spatial-Keyword Queries

Summary: Main-memory spatial-keyword queries are processed with a cost-based optimizer over existing spatial and keyword indexes, avoiding the construction of new index structures. Three plan-building operators and five optimization techniques, with an independence-based approximation guarantee, yield 7–11× lower 99th-percentile latency and outperform single-index baselines and DBMS optimizers. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11430
Venue
VLDB
Year
2016
Pagerank
5.5333985e-05
Overall Rank
7,842 | 46.20%
DOI
10.14778/2850583.2850588

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{lee_vldb16,
        title = {{Processing and Optimizing Main Memory Spatial-Keyword Queries}},
        author = {Lee, Taesung and Hwang, Seung-won and Park, Jin-woo and Lee, Sanghoon and Elnikety, Sameh and He, Yuxiong},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {3},
        pages = {132--143},
        doi = {10.14778/2850583.2850588},
        url = {https://doi.org/10.14778/2850583.2850588},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
7,300 DEX: Query Execution in a Delta-based Storage System 2017 SIGMOD 5.6509215e-05
8,201 List Intersection for Web Search: Algorithms, Cost Models, and Optimizations 2019 VLDB 5.467444e-05
9,472 Indexing for Keyword Search with Structured Constraints 2023 PODS 5.2634238e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

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

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