Abstract
Sentence similarity calculation has an important position in natural language processing and is the basis of text similarity calculation, therefore its accuracy affects the performance of natural language processing. In order to solve the problem of Tibetan sentence similarity calculation, this paper analyzes the contribution of sentence edit distance, sentence structure, sentence length, word order, and the same word to sentence similarity, designs a multi-feature fusion model for Tibetan sentence similarity calculation, proposes a multi-feature fusion method for Tibetan sentence similarity calculation. Experimental results show that the proposed method has achieved good results in Tibetan sentence similarity calculations.
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