Abstract: To accurately express text information by vector and improve the performance of text categorization,a term weighting scheme with enhanced category contribution for text categorization was proposed.Combining the term weighting factor of relevance frequency with the defined category contribution function based on posterior probability,the scheme gave consideration to the description of both category contribution and distributional differences among categories for terms.Experimental results on the four standard corpora show that the proposed scheme do accurately describe the contributions of different features on the classification,optimize the works of text representation and outperform the state-of-the-art methods.