document: A comprehensive comparative study on term weighting schemes for text categorization with support vector machines Term weighting scheme , which has been used to convert the documents as vectors in the term space , is a vital step in automatic text categorization . In this paper , we conducted comprehensive experiments to compare various term weighting schemes with SVM on two widely-used benchmark data sets . We also presented a new term weighting scheme tf-rf to improve the term 's discriminating power . The controlled experimental results showed that this newly proposed tf-rf scheme is significantly better than other widely-used term weighting schemes . Compared with schemes related with tf factor alone , the idf factor does not improve or even decrease the term 's discriminating power for text categorization .
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