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The Power of Two Min-Hashes for Similarity Search among Hierarchical Data Objects

Summary: Sketching/LSH for leaf-labeled hierarchical objects (weighted trees) using min-hash propagation to capture an EMD-like minimum-superimposition distance (set-of-sets view). Prove one propagated min-hash gives poor guarantees while two min-hashes suffice to obtain strong collision-separation properties for similarity search. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1460
Venue
PODS
Year
2008
Pagerank
5.093636e-05
Overall Rank
12,550 | 13.90%
DOI
10.1145/1376916.1376946

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Authors

BibTeX Citation

@inproceedings{gollapudi_pods08,
        address = {New York, NY, USA},
        series = {{PODS} '08},
        title = {{The Power of Two Min-Hashes for Similarity Search among Hierarchical Data Objects}},
        url = {https://dl.acm.org/doi/10.1145/1376916.1376946},
        doi = {10.1145/1376916.1376946},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Gollapudi, Sreenivas and Panigrahy, Rina},
        year = {2008}
}

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

Rank Cited Paper Year Venue Pagerank
21 Similarity Search in High Dimensions via Hashing 1999 VLDB 0.00056760516
1,496 Change Detection in Hierarchically Structured Information 1996 SIGMOD 0.00010569165
4,566 Approximate Matching of Hierarchical Data Using pq-Grams 2005 VLDB 6.6275286e-05
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