@article{Resnik:1999,
  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 = {2007-12-14T02:45:37.000+0100},
  author = {Resnik, Philip},
  biburl = {http://www.bibsonomy.org/bibtex/23d2969db6df305b60ee5ce220045c0cc/diego_ma},
  interhash = {f10519367ccaa8a06ce5bc02ccec3270},
  intrahash = {3d2969db6df305b60ee5ce220045c0cc},
  journal = {Journal of Artificial Intelligence Research},
  keywords = {WordNet semantic_closeness},
  pages = {95-130},
  timestamp = {2007-12-14T02:45:37.000+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
}