Graph-based word sense disambiguation of biomedical documents

Abstract

Motivation: Word Sense Disambiguation (WSD), automatically identifying the meaning of ambiguous words in context, is an important stage of text processing. This article presents a graph-based approach to WSD in the biomedical domain. The method is unsupervised and does not require any labeled training data. It makes use of knowledge from the Unified Medical Language System (UMLS) Metathesaurus which is represented as a graph. A state-of-the-art algorithm, Personalized PageRank, is used to perform WSD. Results: When evaluated on the NLM-WSD dataset, the algorithm outperforms other methods that rely on the UMLS Metathesaurus alone. © The Author 2010. Published by Oxford University Press. All rights reserved.