Knowledge Sources for Word Sense Disambiguation of Biomedical Text

Abstract

Like text in other domains, biomedical documents contain a range of terms with more than one possible meaning. These ambiguities form a significant obstacle to the automatic processing of biomedical texts. Previous approaches to resolving this problem have made use of a variety of knowledge sources including linguistic information (from the context in which the ambiguous term is used) and domain-specific resources (such as UMLS). In this paper we compare a range of knowledge sources which have been previously used and introduce a novel one: MeSH terms. The best performance is obtained using linguistic features in combination with MeSH terms. Results from our system outperform published results for previously reported systems on a standard test set (the NLM-WSD corpus).