A Comprehensive Comparative Study of Word and Sentence Similarity Measures

Abstract

@article{key:article, author = {Issa Atoum and Ahmed Otoom and Narayanan Kulathuramaiyer}, title = {Article: A Comprehensive Comparative Study of Word and Sentence Similarity Measures}, journal = {International Journal of Computer Applications}, year = {2016}, volume = {135}, number = {1}, pages = {10-17}, month = {February}, ABSTRACT Sentence similarity is considered the basis of many natural language tasks such as information retrieval, question answering and text summarization. The semantic meaning between compared text fragments is based on the words' semantic features and their relationships. This article reviews a set of word and sentence similarity measures and compares them on benchmark datasets. On the studied datasets, results showed that hybrid semantic measures perform better than both knowledge and corpus based measures.