%0 Journal Article %1 Li03 %A Li, Yuhua %A Bandar, Zuhair A. %A Mclean, David %C Piscataway, NJ, USA %D 2003 %I IEEE Educational Activities Department %J IEEE Trans. on Knowl. and Data Eng. %K semantic similarity %N 4 %P 871--882 %R http://dx.doi.org/10.1109/TKDE.2003.1209005 %T An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources %U http://dx.doi.org/10.1109/TKDE.2003.1209005 %V 15 %X 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.

@article{Li03, 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.}, added-at = {2009-03-26T12:55:27.000+0100}, address = {Piscataway, NJ, USA}, author = {Li, Yuhua and Bandar, Zuhair A. and Mclean, David}, biburl = {https://www.bibsonomy.org/bibtex/2dc79dd1172250cd936302ab6c00f75b5/mkroell}, citeulike-article-id = {3850810}, doi = {http://dx.doi.org/10.1109/TKDE.2003.1209005}, interhash = {cf273fc35c8c460e481c9b51d42d7058}, intrahash = {dc79dd1172250cd936302ab6c00f75b5}, issn = {1041-4347}, journal = {IEEE Trans. on Knowl. and Data Eng.}, keywords = {semantic similarity}, number = 4, pages = {871--882}, posted-at = {2009-01-05 15:08:48}, priority = {5}, publisher = {IEEE Educational Activities Department}, timestamp = {2009-03-26T12:55:27.000+0100}, title = {An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources}, url = {http://dx.doi.org/10.1109/TKDE.2003.1209005}, volume = 15, year = 2003 }