Measures of semantic similarity and relatedness in the biomedical domain

Measures of semantic similarity between concepts are widely used in Natural Language Processing. In this article, we show how six existing domain-independent measures can be adapted to the biomedical domain. These measures were originally based on WordNet, an English lexical database of concepts and relations. In this research, we adapt these measures to the SNOMED-CTÒ ontology of medical concepts. The measures include two path-based measures, and three measures that augment path-based measures with information content statistics from corpora. We also derive a context vector measure based on medical corpora that can be used as a measure of semantic relatedness. These six measures are evaluated against a newly created test bed of 30 medical concept pairs scored by three physicians and nine medical coders. We find that the medical coders and physicians differ in their ratings, and that the context vector measure correlates most closely with the physicians, while the path-based measur...

• Type: Journal
• Year: 2007
• Where: JBI
• Authors: Ted Pedersen, Serguei V. S. Pakhomov, Siddharth Patwardhan, Christopher G. Chute
• Keywords: Context Vector Measure, JBI 2004, JBI 2007, Medical Coders, Path-based Measures