An experiment was performed at the National Library of Medicine ® (NLM ® ) in word sense disambiguation (WSD) using the Journal Descriptor Indexing (JDI) methodology. The motivation is the need to solve the ambiguity problem confronting NLM’s MetaMap system, which maps free text to terms corresponding to concepts in NLM’s Unified Medical Language System ® (UMLS ® ) Metathesaurus ®. If the text maps to more than one Metathesaurus concept at the same high confidence score, MetaMap has no way of knowing which concept is the correct mapping. We describe the JDI methodology, which is ultimately based on statistical associations between words in a training set of MEDLINE ® citations and a small set of journal descriptors (assigned by humans to journals per se) assumed to be inherited by the citations. JDI is the

This paper explores the effectiveness of unsupervised clustering techniques developed for general English in resolving semantic ambiguities in the biomedical domain. Methods that use first and second order representations of context are evaluated on the National Library of Medicine Word Sense Disambiguation Corpus. We show that the method of clustering second order contexts in similarity space is especially effective on such domain-specific corpora. The significance of the current research lies in the method extension to a new, previously untested domain and the general exploration of method portability across domains. 1

Abstract. We present an ontology-driven word sense disambiguation process. The main idea consists of using the context of the ambiguous word to decide which class can be assigned to it. The disambiguation relies on similarities between classes assigned to the ambiguous word, classes assigned to terms close to it in the text, and on the type of properties that could occur between them. The computation of the similarity uses domain ontologies to provide semantic distances based on definitions in intension. We tested our approach in the extraction of annotations from biomedical texts.

This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. ProfileGrids as a new visual representation of large multiple sequence alignments: a case study of the RecA protein family BMC Bioinformatics 2008, 9:554 doi:10.1186/1471-2105-9-554

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