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Efficient RkNN Retrieval with Arbitrary Non-Metric Similarity Measures

Summary: RkNN under arbitrary non-metric dissimilarities, where query-time aggregation over attribute distances defines the distance. Uses AL-Tree for group-level reasoning to prune RkNN, beating naive scans and block-based methods on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10250
Venue
VLDB
Year
2010
Pagerank
5.093636e-05
Overall Rank
12,463 | 14.50%
DOI
10.14778/1920841.1920999

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BibTeX Citation

@article{p_vldb10,
        title = {{Efficient RkNN Retrieval with Arbitrary Non-Metric Similarity Measures}},
        author = {P, Deepak and Deshpande, Prasad M},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {1243--1254},
        doi = {10.14778/1920841.1920999},
        url = {https://doi.org/10.14778/1920841.1920999},
        year = {2010}
}

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