期刊論文

學年 99
學期 1
出版(發表)日期 2010-08-01
作品名稱 Chinese text classification by the Naïve Bayes Classifier and the associative classifier with multiple confidence threshold values
作品名稱(其他語言)
著者 Lu, Shing-Hwa; Chiang, Ding-An; Keh, Huan-Chao; Huang, Hui-Hua
單位 淡江大學資訊工程學系
出版者 Amsterdam: Elsevier BV
著錄名稱、卷期、頁數 Knowledge-Based Systems 23(6), pp. 598–604
摘要 Each type of classifier has its own advantages as well as certain shortcomings. In this paper, we take the advantages of the associative classifier and the Naïve Bayes Classifier to make up the shortcomings of each other, thus improving the accuracy of text classification. We will classify the training cases with the Naïve Bayes Classifier and set different confidence threshold values for different class association rules (CARs) to different classes by the obtained classification accuracy rate of the Naïve Bayes Classifier to the classes. Since the accuracy rates of all selected CARs of the class are higher than that obtained by the Naïve Bayes Classifier, we could further optimize the classification result through these selected CARs. Moreover, for those unclassified cases, we will classify them with the Naïve Bayes Classifier. The experimental results show that combining the advantages of these two different classifiers better classification result can be obtained than with a single classifier.
關鍵字 Association classification; Text classification; Text mining; Text categorization
語言 en
ISSN 0950-7051
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者 Huang, Hui-Hua
審稿制度
國別 NLD
公開徵稿
出版型式 紙本
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