Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language

by: Philip Resnik

Journal of Artificial Intelligence Research, Vol. 11 (1999), pp. 95-130.

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摘要

This paper presents a measure of semantic similarity in an is-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs significantly better than the traditional edge counting approach. The paper presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.

@article{citeulike:160043, abstract = {This paper presents a measure of semantic similarity in an is-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs significantly better than the traditional edge counting approach. The paper presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.}, author = {Resnik, Philip }, citeulike-article-id = {160043}, journal = {Journal of Artificial Intelligence Research}, keywords = {semantic-similarity}, pages = {95--130}, posted-at = {2005-04-13 21:47:02}, priority = {3}, title = {Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language}, url = {http://citeseer.ist.psu.edu/resnik99semantic.html}, volume = {11}, year = {1999} }

RIS record

TY - JOUR ID - citeulike:160043 L3 - citeulike-article-id:160043 N2 - This paper presents a measure of semantic similarity in an is-a taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs significantly better than the traditional edge counting approach. The paper presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness. JF - Journal of Artificial Intelligence Research EP - 130 TI - Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language VL - 11 SP - 95 KW - semantic-similarity AU - Resnik, Philip PY - 1999/// UR - http://citeseer.ist.psu.edu/resnik99semantic.html ER -

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