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)
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 |
|---|---|---|---|---|
| 4,894 | triCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data | 2005 | SIGMOD | 6.3677123e-05 |
| 4,972 | Computing Clusters of Correlation Connected Objects | 2004 | SIGMOD | 6.3318975e-05 |
| 5,632 | Combi-Operator – Database Support for Data Mining Applications | 2003 | VLDB | 6.0581466e-05 |
| 8,383 | CURLER: Finding and Visualizing Nonlinear Correlation Clusters | 2005 | SIGMOD | 5.3425512e-05 |
| 8,914 | Advancing Data Clustering via Projective Clustering Ensembles | 2011 | SIGMOD | 5.2559789e-05 |
| 8,941 | Evaluating Clustering in Subspace Projections of High Dimensional Data | 2009 | VLDB | 5.254732e-05 |
| 13,054 | k-Means Projective Clustering | 2004 | PODS | 4.9793485e-05 |
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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 | 0.00049737458 |
| 94 | Efficient and Effective Clustering Methods for Spatial Data Mining | 1994 | VLDB | 0.00034579889 |
| 308 | Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications | 1998 | SIGMOD | 0.00021473921 |
| 363 | CURE: An Efficient Clustering Algorithm for Large Databases | 1998 | SIGMOD | 0.00019987463 |
| 1,634 | Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces | 2000 | VLDB | 0.0001001862 |
| 1,679 | Fast Algorithms for Projected Clustering | 1999 | SIGMOD | 9.9079414e-05 |
| 1,881 | Finding Generalized Projected Clusters in High Dimensional Spaces | 2000 | SIGMOD | 9.4403736e-05 |
| 2,113 | What is the nearest neighbor in high dimensional spaces? | 2000 | VLDB | 9.0196806e-05 |
| 3,740 | Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering | 1999 | VLDB | 7.0595359e-05 |
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