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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/45517


    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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