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A Comprehensive Comparative Study of Word and Sentence Similarity Measures

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Issa Atoum, Ahmed Otoom, Narayanan Kulathuramaiyer
10.5120/ijca2016908259

Issa Atoum, Ahmed Otoom and Narayanan Kulathuramaiyer. Article: A Comprehensive Comparative Study of Word and Sentence Similarity Measures. International Journal of Computer Applications 135(1):10-17, February 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@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},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

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.

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Keywords

Word Similarity, Sentence Similarity, Corpus Measures, Knowledge Measures, Hybrid Measures, Text Similarity