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High-Throughput k Nearest Neighbors Search in Road Networks

Summary: Local subgraph-based kNN indexing for road networks under frequent inserts/deletes, targeting throughput rather than just latency. Updates touch only affected subgraphs; queries incrementally explore boundary vertices with a correctness proof that local info suffices for global kNN. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID
7673
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,460 | 28.24%
DOI
10.1145/3786656

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BibTeX Citation

@inproceedings{kong_sigmod26,
        title = {{High-Throughput k Nearest Neighbors Search in Road Networks}},
        author = {Kong, Yu and Chang, Lijun and Wen, Dong and Ouyang, Dian},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3786656},
        url = {https://dl.acm.org/doi/10.1145/3786656},
        year = {2026}
}

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