Li, Yuhua and Bandar, Zuhair A. and McLean, David A. (2003) An approach for measuring semantic similarity between words using multiple information sources. ISSN 1041-4347Full text not available from this repository.
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.
|Additional Information:||Full-text of this article is not available in this e-prints service. This article was originally published following peer-review in IEEE Transactions on Knowledge and Data Engineering, published by and copyright IEEE.|
|Divisions:||Legacy Research Institutes > Dalton Research Institute > Computer Science|
|Date Deposited:||16 Sep 2009 13:07|
|Last Modified:||01 Sep 2016 13:56|
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