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Advancing Data Clustering via Projective Clustering Ensembles

Summary: Single-objective PCE unifies object- and feature-based representations via distance to the ensemble, addressing independence issues of two-objective PCE. Two cluster-based approximations align with standard ensemble paradigms; benchmarks show improved results over prior PCE methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4427
Venue
SIGMOD
Year
2011
Pagerank
4.4937074e-05
Overall Rank
8,547 | 40.55%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,331 The Gibbs–Rand Model 2022 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,595 Fast Algorithms for Projected Clustering 1999 SIGMOD 0.00011222442
3,376 A Monte Carlo Algorithm for Fast Projective Clustering 2002 SIGMOD 7.1630476e-05
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