Abstract: At present, there is a certain gap between the calculation results of semantic similarity of words and the results of artificial discrimination, mainly because the semantic similarity calculation based on knowledge ontology generally uses the semantic classification dictionary directly from the perspective of mathematical calculation, but does not make full use of the linguistic knowledge in the dictionary from the perspective of lexicology. Therefore, we use the theory of semantic field to analyze the organizational relationship between words in Cilin, and expound the decisive role of depth in semantic similarity and the auxiliary role of branch information. On the basis of the combination of depth with branch information of Cilin, the Logistic function calculation model is proposed. The Pearson correlation coefficient between the calculated result of semantic similarity of MC30 and the manually labeled value is 0.9540; the average root error is 0.0191; the Pearson correlation coefficient between the calculated result of semantic similarity of RG65 and the manually labeled value is 0.9434; the average root error is 0.0193.

Key words: semantic similarity, Cilin, depth, Logistic function