A Sentence Similarity Computation for Restricted Domain

Abstract

To improve the accuracy of sentence similarity computation in automatic question answering system for restricted domain, this paper proposed a new TextRank-RD algorithm based on vector space model. The algorithm assigns the node an initial value based on three factors: whether the domain dictionary contains the word, whether the word is a none, the position of the word. And it uses a weighted graph model that assigns weights according to the importance of nodes rather than an unweighted graph model that assigns weights equally. The experimental results show that the algorithm improved the accuracy of sentence similarity calculation compared with the TF-IDF algorithm based on vector space model, and this has important significance to improve the efficiency of the automatic question answering system for restricted domain.