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Programmable Clustering

Summary: Introduce "programmable clustering": users specify acceptable clusterings via first-order logic formulas rather than an explicit objective. Show the general problem can be NP-hard but identify three FO specifications that admit efficient algorithms and give solutions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1406
Venue
PODS
Year
2006
Pagerank
-
Overall Rank
13,810 | 5.26%
DOI
10.1145/1142351.1142400

Incoming Non-self Citations Over Time

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Authors

BibTeX Citation

@inproceedings{gollapudi_pods06,
        address = {New York, NY, USA},
        series = {{PODS} '06},
        title = {{Programmable Clustering}},
        url = {https://dl.acm.org/doi/10.1145/1142351.1142400},
        doi = {10.1145/1142351.1142400},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Gollapudi, Sreenivas and Kumar, Ravi and Sivakumar, D.},
        year = {2006}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
9,402 Approximation Algorithms for Co-Clustering 2008 PODS 5.2755515e-05
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