A New Approach for Calculating Semantic Similarity between Words Using WordNet and Set Theory

Abstract

Calculating semantic similarity between words is a challenging task of a lot of domains such as Natural language processing (NLP), information retrieval and plagiarism detection. WordNet is a lexical dictionary conceptually organized, where each concept has several characteristics: Synsets and Glosses. Synset represent sets of synonyms of a given word and Glosses are a short description. In this paper, we propose a new approach for calculating semantic similarity between two concepts. The proposed method is based on set theory's concepts and WordNet properties, by calculating the relatedness between the synsets' and glosses's of the two concepts.