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

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.

• Type: Journal
• Year: 2011
• Where: CORR
• Authors: Philip Resnik
• Keywords: CORR 2011, Education, Human Similarity Judgments, Semantic Similarity, Traditional Edge-counting Approach