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ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
14 years 2 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
14 years 1 months ago
MaPle: A Fast Algorithm for Maximal Pattern-based Clustering
Pattern-based clustering is important in many applications, such as DNA micro-array data analysis, automatic recommendation systems and target marketing systems. However, pattern-...
Jian Pei, Xiaoling Zhang, Moonjung Cho, Haixun Wan...
KDD
2002
ACM
134views Data Mining» more  KDD 2002»
14 years 8 months ago
Discovering word senses from text
Categories and Subject Descriptors Information Storage and Retrieval Clustering General Terms Keywords
Patrick Pantel, Dekang Lin
STOC
2002
ACM
103views Algorithms» more  STOC 2002»
14 years 8 months ago
Approximate clustering via core-sets
In this paper, we show that for several clustering problems one can extract a small set of points, so that using those core-sets enable us to perform approximate clustering effici...
Mihai Badoiu, Sariel Har-Peled, Piotr Indyk
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...