The Chinese text categorization system with association rule and category priority

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Title:	The Chinese text categorization system with association rule and category priority
Authors:	蔣定安;Chiang, Ding-an;Keh, Huan-chao;Huang, Hui-hua;Chyr, Derming
Contributors:	淡江大學資訊工程學系
Keywords:	Text categorization;Feature selection;Filtering measure;Text mining;Association rule
Date:	2008-07-08
Issue Date:	2010-08-10 10:42:08 (UTC+8)
Publisher:	Oxford: Pergamon
Abstract:	The process of text categorization involves some understanding of the content of the documents and/or some previous knowledge of the categories. For the content of the documents, we use the filtering measure for feature selection in our Chinese text categorization system. We modify the formula of TFIDF to strengthen important keywords’ weights and weaken unimportant keywords’ weights. For the knowledge of the categories, we use association rules to improve the precision of text classification and use category priority to represent the relationship between two different categories. Consequently, the experimental results show that our method can effectively not only decrease noise text but also increase the ratio of precision and recall of text categorization.
Relation:	Expert Systems with Applications 35(1-2), pp.102-110
DOI:	10.1016/j.eswa.2007.06.019
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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