A Monte Carlo Algorithm for Fast Projective Clustering

Summary: Monte Carlo algorithm for fast projective clustering, with an optimal density-based subspace formulation and high-probability guarantees. Heuristics speed computation; experiments show improved accuracy vs prior work. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h65b51c934415537c
Venue: SIGMOD
Year: 2002
Pagerank: 7.1525532e-05
Overall Rank: 3,618 | 75.69%
DOI: 10.1145/564691.564739

Incoming Non-self Citations Over Time

Authors

1. Cecilia M. Procopiuc (AT&T)
2. Michael Jones (Mitsubishi Electric Company)
3. Pankaj K. Agarwal (Duke University)
4. T. M. Murali (Boston University)

BibTeX Citation

@inproceedings{procopiuc_sigmod02,
        title = {{A Monte Carlo Algorithm for Fast Projective Clustering}},
        author = {Procopiuc, Cecilia M. and Jones, Michael and Agarwal, Pankaj K. and Murali, T. M.},
        series = {{SIGMOD} '02},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/564691.564739},
        url = {https://dl.acm.org/doi/10.1145/564691.564739},
        year = {2002}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,895	triCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data	2005	SIGMOD	6.3646979e-05
4,974	Computing Clusters of Correlation Connected Objects	2004	SIGMOD	6.3289112e-05
5,634	Combi-Operator – Database Support for Data Mining Applications	2003	VLDB	6.0552789e-05
8,388	CURLER: Finding and Visualizing Nonlinear Correlation Clusters	2005	SIGMOD	5.3400228e-05
8,922	Advancing Data Clustering via Projective Clustering Ensembles	2011	SIGMOD	5.2534908e-05
8,949	Evaluating Clustering in Subspace Projections of High Dimensional Data	2009	VLDB	5.2522445e-05
13,060	k-Means Projective Clustering	2004	PODS	4.9769913e-05

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
32	BIRCH: An Efficient Data Clustering Method for Very Large Databases	1996	SIGMOD	0.00049714561
94	Efficient and Effective Clustering Methods for Spatial Data Mining	1994	VLDB	0.0003456395
308	Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications	1998	SIGMOD	0.00021463972
364	CURE: An Efficient Clustering Algorithm for Large Databases	1998	SIGMOD	0.00019978187
1,634	Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces	2000	VLDB	0.00010013999
1,679	Fast Algorithms for Projected Clustering	1999	SIGMOD	9.90334e-05
1,882	Finding Generalized Projected Clusters in High Dimensional Spaces	2000	SIGMOD	9.4359061e-05
2,114	What is the nearest neighbor in high dimensional spaces?	2000	VLDB	9.0164212e-05
3,743	Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering	1999	VLDB	7.0562784e-05

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