%0 Journal Article %1 resnik1998semantic %A Resnik, Philip %D 1998 %J Journal of Artificial Intelligence Research %K WordNet closeness semantics %P 95-130 %T Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language %U http://www.cs.washington.edu/research/jair/abstracts/resnik99a.html %V 11 %X This article 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 better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.

@article{resnik1998semantic, abstract = {This article 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 better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.}, added-at = {2017-12-16T18:34:05.000+0100}, author = {Resnik, Philip}, biburl = {https://www.bibsonomy.org/bibtex/23d2969db6df305b60ee5ce220045c0cc/thoni}, interhash = {f10519367ccaa8a06ce5bc02ccec3270}, intrahash = {3d2969db6df305b60ee5ce220045c0cc}, journal = {Journal of Artificial Intelligence Research}, keywords = {WordNet closeness semantics}, pages = {95-130}, timestamp = {2017-12-17T15:05:57.000+0100}, title = {Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language}, url = {http://www.cs.washington.edu/research/jair/abstracts/resnik99a.html}, volume = 11, year = 1998 }