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» Approximation Algorithms for Clustering Problems
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ICPR
2008
IEEE
16 years 7 months ago
Multiclass spectral clustering based on discriminant analysis
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Xi Li, Zhongfei Zhang, Yanguo Wang, Weiming Hu
ICML
2006
IEEE
16 years 7 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani
WWW
2006
ACM
16 years 7 months ago
Using symbolic objects to cluster web documents
Web Clustering is useful for several activities in the WWW, from automatically building web directories to improve retrieval performance. Nevertheless, due to the huge size of the...
Esteban Meneses, Oldemar Rodríguez-Rojas
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
16 years 21 days ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester
COCOON
2004
Springer
15 years 10 months ago
k-Center Problems with Minimum Coverage
In this work, we study an extension of the k-center facility location problem, where centers are required to service a minimum of clients. This problem is motivated by requirement...
Andrew Lim, Brian Rodrigues, Fan Wang, Zhou Xu