Text similarity algorithm based on semantic vector space model

Abstract

In this paper, a text similarity computation method named VSM-Cilin which is based on semantic vector space model is proposed in the background of radio station. VSM-Cilin improved the traditional VSM in the following areas. First, consider the semantic relations between words. Second, use semantic resources to reduce dimension. Third, use inverted index to filter out candidate document set. Forth, take the weight of the feature item into consideration when compute the similarity. The experiments show that the accuracy of VSM-Cilin is significantly improved compared with the traditional vector space model and the method of bidirectional mapping based on HITIR-Lab Tongyici Cilin.