代六玲,黄河燕,陈肇雄. 中文文本分类中特征抽取方法的比较研究[J]. 中文信息学报, 2004, 18(1): 27-33.
DAI Liu-ling,HUANG He-yan,CHEN Zhao-xiong. A Comparative Study on Feature Selection in Chinese Text Categorization. , 2004, 18(1): 27-33.
中文文本分类中特征抽取方法的比较研究
代六玲1,2,黄河燕2,陈肇雄2
1.南京理工大学计算机科学系 2.中国科学院计算机语言信息工程研究中心
A Comparative Study on Feature Selection in Chinese Text Categorization
DAI Liu-ling1,2,HUANG He-yan2,CHEN Zhao-xiong2
1.Department of Computer Science , NUST 2.Language Information Engineering , CAS
Abstract：This paper is a comparative study of feature selection methods in text categorization. Four methods were evaluated, including document frequency (DF) , information gain (IG) , mutual information (MI) and χ2-test (CHI) . A Support Vector Machine (SVM) and a k-nearest neighbor (KNN) were selected as the evaluating classifiers. We found IG, MI and CHI had poor performance in our test , though they behave well in English text categorization. We analyzed the reasons theoretically and put forwarded the possible solutions. A furthermore experiment proved that the combined feature selection method is effective.
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