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ICML
2004
IEEE
16 years 8 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
KDD
2006
ACM
167views Data Mining» more  KDD 2006»
16 years 7 months ago
Clustering pair-wise dissimilarity data into partially ordered sets
Ontologies represent data relationships as hierarchies of possibly overlapping classes. Ontologies are closely related to clustering hierarchies, and in this article we explore th...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...
WSDM
2009
ACM
172views Data Mining» more  WSDM 2009»
16 years 2 months ago
Clustering the tagged web
Automatically clustering web pages into semantic groups promises improved search and browsing on the web. In this paper, we demonstrate how user-generated tags from largescale soc...
Daniel Ramage, Paul Heymann, Christopher D. Mannin...
ICCD
1997
IEEE
100views Hardware» more  ICCD 1997»
15 years 11 months ago
Optimal Clock Period Clustering for Sequential Circuits with Retiming
Abstract— In this paper we consider the problem of clustering sequential circuits subject to a bound on the area of each cluster, with the objective of minimizing the clock perio...
Arvind K. Karandikar, Peichen Pan, C. L. Liu
IS
2008
15 years 7 months ago
Continuous subspace clustering in streaming time series
Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...