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Closest Pairs Search Over Data Stream

Summary: Introduces k-closest pair (KCP) search over streaming data, enabling incremental maintenance for arbitrary k. Proposes NNS (Nearest-Neighbor Set) and TNNS, plus a tau-DLBP partition, to access only O(k) objects and support efficient KCP updates on data streams. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h18ca9841f8352823
Venue
SIGMOD
Year
2023
Pagerank
4.9793485e-05
Overall Rank
11,722 | 21.19%
DOI
10.1145/3617326

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{zhu_sigmod23,
        title = {{Closest Pairs Search Over Data Stream}},
        author = {Zhu, Rui and Wang, Bin and Yang, Xiaochun and Zheng, Baihua},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3617326},
        url = {https://dl.acm.org/doi/10.1145/3617326},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,405 Adaptive Outlier Detection over Data Stream 2026 SIGMOD 4.9793485e-05
10,787 Continuous Query for Top-K Maximal Sum Intervals over Streaming Data 2026 VLDB 4.9793485e-05
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