A Comprehensive Comparative Study of Word and Sentence Similarity Measures

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.

• Publication year

  2016

• Venue

  arXiv.org

• Publication date

  2016-02-17

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.5120/ijca2016908259arXiv 1610.04533
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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