Combining Common Words and Semantic Features for Sentence Similarity

Abstract

Assessing the similarity of short texts or sentences is an important phase in many natural processing activities. The paper describes the importance and role of sentence similarity in various domains and also the paper provides a mechanism to calculate the similarity between short texts. The main idea in this paper is to extract the syntactic and semantic features between the sentences, to calculate the similarity between them. The syntactic features are evaluated by finding the common words between the sentences, whereas the semantic features are evaluated using the information content between the concepts of the sentences. For obtaining the information content between the concepts knowledge based measures are used. Three information content based measures are compared in this paper over bench mark sentence similarity dataset. The results show that the integration of syntactic and semantic features increases the performance of the system.