An approach for measuring semantic similarity between words using multiple information sources
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 lex...
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Veröffentlicht in: | IEEE transactions on knowledge and data engineering 2003-07, Vol.15 (4), p.871-882 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 1041-4347 1558-2191 |
DOI: | 10.1109/TKDE.2003.1209005 |