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BMCBI
2004
181views more  BMCBI 2004»
13 years 4 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
CIKM
2004
Springer
13 years 10 months ago
Document clustering based on cluster validation
This paper presents a cluster validation based document clustering algorithm, which is capable of identifying both important feature words and true model order (cluster number). I...
Zheng-Yu Niu, Dong-Hong Ji, Chew Lim Tan
CIVR
2006
Springer
143views Image Analysis» more  CIVR 2006»
13 years 8 months ago
Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval
Abstract. This paper presents novel dissimilarity space specially designed for interactive multimedia retrieval. By providing queries made of positive and negative examples, the go...
Eric Bruno, Nicolas Moënne-Loccoz, Sté...
ICDAR
2003
IEEE
13 years 10 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
IMCSIT
2010
13 years 2 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