relation: https://khub.utp.edu.my/scholars/1005/
title: A proposed hybrid approach for feature selection in text document categorization
creator: Zaiyadi, M.F.
creator: Baharudin, B.
description: Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.
date: 2010
type: Article
type: PeerReviewed
identifier:   Zaiyadi, M.F. and Baharudin, B.  (2010) A proposed hybrid approach for feature selection in text document categorization.  World Academy of Science, Engineering and Technology, 72.  pp. 137-141.  ISSN 2010376X     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651593676&partnerID=40&md5=c59ed4f89ed18c5bff83ca741a230819