期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2013
卷号：3
期号：6
DOI：10.5121/ijdkp.2013.3606
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Automatic Text categorization refers to the process of assigning a category or some categories automatically among predefined ones. Text categorization is challenging in Indian languages has rich in morphology, a large number of word forms and large feature spaces. This paper investigates the performance of different classification approaches using different term weighting approaches in order to decide the most applicable one to Telugu text classification problem. We have investigated on different term weighting methods for Telugu corpus in combination with Naive Bayes ( NB), Support Vector Machine (SVM) and k Nearest Neighbor (kNN) classifiers
关键词：Term Weighting Methods; Text Categorization; Support Vector Machine; Naive Bayes; k Nearest Neighbor; ;CHI-square
