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

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 e ectiveness.

DOI: 10.1613/jair.514

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@article{Resnik1999SemanticSI, title={Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language}, author={Philip Resnik}, journal={J. Artif. Intell. Res.}, year={1999}, volume={11}, pages={95-130} }