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» An Evaluation on Feature Selection for Text Clustering
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ICML
2003
IEEE
13 years 10 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma
ICONIP
2008
13 years 6 months ago
Local Feature Selection in Text Clustering
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...
CIARP
2010
Springer
13 years 3 months ago
Improving the Dynamic Hierarchical Compact Clustering Algorithm by Using Feature Selection
Abstract. Feature selection has improved the performance of text clustering. In this paper, a local feature selection technique is incorporated in the dynamic hierarchical compact ...
Reynaldo Gil-García, Aurora Pons-Porrata
IMCSIT
2010
13 years 1 months ago
Evaluation of Clustering Algorithms for Polish Word Sense Disambiguation
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focu...
Bartosz Broda, Wojciech Mazur
CSIE
2009
IEEE
13 years 11 months ago
Evaluating Clustering Algorithms: Cluster Quality and Feature Selection in Content-Based Image Clustering
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
Mesfin Sileshi, Björn Gambäck