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Measuring semantic similarity between words using lexical knowledge and neural networks

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Li, Yuhua, Bandar, Zuhair and Mclean, David (2002) Measuring semantic similarity between words using lexical knowledge and neural networks. SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY. 6 pp ISBN 3-540-44025-9 [Book (authored)]

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Abstract

This paper investigates the determination of semantic similarity by the incorporation of structural semantic knowledge from a lexical database and the learning ability of neural networks. The lexical database is assumed to be organised in a hierarchical structure. The extracted lexical knowledge contains the relative location of the concerned words in the lexical hierarchy. The neural network then processes available lexical knowledge to provide semantic similarity for words. Experimental evaluation against a benchmark set of human similarity ratings demonstrates that the proposed method is effective in measuring semantic similarity between words.

Item Type:Book (authored)
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:5975
Deposited By:Dr Yuhua Li
Deposited On:09 Mar 2010 16:15
Last Modified:09 Mar 2010 16:15

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