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Improved term selection algorithm based on variance in text categorization
Proceedings of the 2nd International Conference On Systems Engineering and Modeling
This article improves the algorithm of term weighting in automated text classification. The traditional TFIDF algorithm is a common method that is used to measure term weighting in text classification.However, the algorithm does not take the distribution of terms in inter-class. In order to solve the problem, variance which describes the distribution of terms in inter-class and intra-class is used to revise TFIDF algorithm. This article mainly researched about the construction of LFHW term setsdoi:10.2991/icsem.2013.157 fatcat:ugcgbfxudjb6ldbu5z4nirzjgm