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In automatic text categorization, the influence of features on the decision is set by the term weights which are conventionally computed as the product of term frequency and collection frequency factors. The raw form of term frequencies or their logarithmic forms are generally used as the term frequency factor whereas the leading collection frequency factors take into account the document frequency of each term. In this study, it is firstly shown that the best-fitting form of the term frequencydoi:10.1016/j.engappai.2012.06.013 fatcat:gz4tm5zhhzfinlsrqpvui5v7fa