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Sentence similarity computing based on the “HowNet” usually treats the optimal matches between the primitives or words as the basic computing unit, and the final results can be got through the weighted sum model. However, this approach often results in the information duplication and the irrational construction. For such problems, this paper calculates the similarity of sets through the statistics of common information (commonality) and the different information (differences) between the two sets of direct primitives. Moreover, the paper introduces this measure into the calculation of sentence similarity. The final experimental analysis shows that the method used in this paper is more stable and effective.