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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/54954

    Title: The Chinese Text Categorization System with Category Priorities
    Authors: Keh, Huan-Chao;Chiang, Ding-An;Hsu, Chih-Cheng;Huang, Hui-Hua
    Contributors: 淡江大學資訊工程學系
    Keywords: text categorization;feature selection;filtering measure;text mining
    Date: 2010-10
    Issue Date: 2013-06-13 11:29:44 (UTC+8)
    Publisher: Oulu: Academy Publisher
    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 a filtering measure for feature selection in our Chinese text categorization system. We modify the formula of Term Frequency-Inverse Document Frequency (TF-IDF) to strengthen important keywords’ weights and weaken unimportant keywords’ weights. For the knowledge of the categories, we 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 accuracy rate and recall rate of text categorization.
    Relation: Journal of Software 5(10), pp.1137-1143
    DOI: 10.4304/jsw.5.10.1137-1143
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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