Abstract: In recent years,latent dirichlet allocation(LDA)topic model provides a new idea for short text similarity calculation by mining the latent semantic themes of text.In view of the sparse features of short text,because the application of LDA theme model may easily lead to inaccurate results of similarity computation,this paper presented a calculation method based on LDA model combining similarity topics factor ST and co-occurrence words factor CW to establish union similarity model.In the protocol of different ST intervals,CW generates constraint or supplementary conditions to ST,and obtains higher accuracy of text similarity.A text clustering experiment was used to verify the method.The experimental results show that the proposed method gains a certain improvement of F measure value

Key words: Co-occurence words, LDA, Short text similarity, Similarity topics, Topic model