Authors : S. M. Kamruzzaman and Chowdhury Mofizur Rahman
Abstract: As the amount of online text increases, the demand for text categorization to aid the analysis and management of text is increasing. Text is cheap, but information, in the form of knowing what classes a text belongs to, is expensive. Automatic categorization of text can provide this information at low cost, but the classifiers themselves must be built with expensive human effort, or trained from texts which have themselves been manually classified. Text categorization using Association Rule and Na?ve Bayes Classifier is proposed here. Instead of using words word relation i.e association rules from these words is used to derive feature set from pre-classified text documents. Na?ve Bayes Classifier is then used on derived features for final categorization.
S. M. Kamruzzaman and Chowdhury Mofizur Rahman , 2004. Text Categorization using Association Rule and Na?ve Bayes Classifier . Asian Journal of Information Technology, 3: 657-665.