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A Comprehensive Comparative Study of Word and Sentence Similarity Measures
February 17, 2016 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Issa Atoum, Ahmed Otoom, Narayanan Kulathuramaiyer
arXiv ID
1610.04533
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL
Citations
14
Venue
arXiv.org
Last Checked
4 months ago
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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