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Towards Proximity Pattern Mining in Large Graphs

Summary: Proximity patterns: neighborhood-label co-occurrence, a relaxed alternative to frequent subgraphs blending itemset efficiency with graph proximity. NmPA transforms graph mining to probabilistic itemset mining solvable by pFP, enabling scalable discovery on large networks and exposing patterns ignored by previous work. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4362
Venue
SIGMOD
Year
2010
Pagerank
6.2318138e-05
Overall Rank
5,401 | 62.95%
DOI
10.1145/1807167.1807261

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{khan_sigmod10,
        title = {{Towards Proximity Pattern Mining in Large Graphs}},
        author = {Khan, Arijit and Yan, Xifeng and Wu, Kun-Lung},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807261},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807261},
        year = {2010}
}

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