|Title: ||An approach for measuring semantic similarity between words using multiple information sources|
|Citation: ||IEEE transactions on knowledge and data engineering, 2003, vol. 15, no. 4, pp. 871-882|
|Issue Date: ||2003 |
|Additional Links: ||http://www2.computer.org/portal/web/tkde|
|Abstract: ||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.|
|Description: ||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.|
|Appears in Collections: ||Computer Science|
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