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An Approximate Search Engine for Structural Databases

Summary: Proposes an approximate search engine for structural databases, trading exact isomorphism for fast, approximate matching. Applies to trees, graphs, and labelled point sets (proteins, phylogenies, XML) via compact heuristics for near-instant comparisons. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3296
Venue
SIGMOD
Year
2000
Pagerank
9.0950687e-05
Overall Rank
2,143 | 85.30%
DOI
10.1145/342009.335495

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_sigmod00,
        title = {{An Approximate Search Engine for Structural Databases}},
        author = {Wang, Jason T. L. and Wang, Xiong and Shasha, Dennis and Shapiro, Bruce A. and Zhang, Kaizhong and Ma, Qicheng and Weinberg, Zasha},
        series = {{SIGMOD} '00},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/342009.335495},
        url = {https://dl.acm.org/doi/10.1145/342009.335495},
        year = {2000}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
37 DISCOVER: Keyword Search in Relational Databases 2002 VLDB 0.00048017193
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Outgoing Citations (Sorted by Pagerank)

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

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