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An approach for measuring semantic similarity between words using multiple information sources

Li, Yuhua, Bandar, Zuhair and McLean, David (2003) An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering, 15 (4). pp. 871-882. [Journal article]

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URL: http://csdl2.computer.org/persagen/DLAbsToc.jsp?resourcePath=/dl/trans/tk/&toc=comp/trans/tk/2003/04/k4toc.xml&DOI=10.1109/TKDE.2003.1209005


Semantic similarity between words is becoming a generic problem for many applications of computational linguistics and artificial intelligence. This paper explores the determination of semantic similarity by a number of information sources, which consist of structural semantic information from a lexical taxonomy and information content from a corpus. To investigate how information sources could be used effectively, a variety of strategies for using various possible information sources are implemented. A new measure is then proposed which combines information sources nonlinearly. Experimental evaluation against a benchmark set of human similarity ratings demonstrates that the proposed measure significantly outperforms traditional similarity measures.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:8638
Deposited By: Dr Yuhua Li
Deposited On:03 Feb 2010 11:30
Last Modified:09 May 2016 10:55

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