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SILKMOTH: An Efficient Method for Finding Related Sets with Maximum Matching Constraints

Summary: SILKMOTH efficiently discovers set pairs related by similarity-weighted maximum matching, while preserving exact brute-force results. Signature-based pruning, novel filters, and triangle-inequality acceleration yield an order-of-magnitude speedup across broad similarity metrics. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11582
Venue
VLDB
Year
2017
Pagerank
6.552423e-05
Overall Rank
4,707 | 67.71%
DOI
10.14778/3115404.3115413

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BibTeX Citation

@article{deng_vldb17,
        title = {{SILKMOTH: An Efficient Method for Finding Related Sets with Maximum Matching Constraints}},
        author = {Deng, Dong and Kim, Albert and Madden, Samuel and Stonebraker, Michael},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {10},
        pages = {1082--1093},
        doi = {10.14778/3115404.3115413},
        url = {https://doi.org/10.14778/3115404.3115413},
        year = {2017}
}

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