DBScholar

Back to papers

Connected Substructure Similarity Search

Summary: Proposes GrafD-Index for connected substructure search, indexing graphs by feature-distance and deriving a tight distance-triangle inequality. Derives bounds to prune candidates and accelerate verification, with strong experimental gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4365
Venue
SIGMOD
Year
2010
Pagerank
7.5353184e-05
Overall Rank
3,311 | 77.29%
DOI
10.1145/1807167.1807264

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{shang_sigmod10,
        title = {{Connected Substructure Similarity Search}},
        author = {Shang, Haichuan and Lin, Xuemin and Zhang, Ying and Yu, Jeffrey Xu and Wang, Wei},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807264},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807264},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers