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

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 Gloss...

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Bibliographic Details
Published in:Procedia computer science 2019, Vol.151, p.1261-1265
Main Authors: EZZIKOURI, Hanane, MADANI, Youness, ERRITALI, Mohammed, OUKESSOU, Mohamed
Format: Article
Language:English
Subjects:
Natural Language Processing
Semantic Similarity
Set Theory
WordNet
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Summary: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.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2019.04.182