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Unformatted text preview: Irena Spasic is a postdoctoral research associate in the School of Chemistry and the Manchester Interdisciplinary Biocentre at the University of Manchester. Her research interests include biomedical text mining, machine learning and bioinformatics. Sophia Ananiadou is co-director of the UK National Centre for Text Mining and a Reader in Computer Science at the University of Salford. Her research interests are in the areas of computational terminology and biomedical text mining. John McNaught is a Lecturer in the School of Informatics at the University of Manchester and an Associate Director of the UK National Centre for Text Mining. His research interests include information extraction and computational lexicography. Anand Kumar is Alexander von Humboldt research fellow in the Faculty of Medicine at the University of Leipzig and a member of the Institute for Formal Ontology and Medical Information Science at Saarland University in Saarbru ¨cken. His research interests include medical and biomedical knowledge representation, data models and ontologies. Keywords: text mining, ontology, terminology, information extraction, information retrieval Irena Spasic, School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester M60 1QD,UK Tel: þ 44 (0)161 306 4414 Fax: þ 44 (0)161 306 4556 E-mail: firstname.lastname@example.org Text mining and ontologies in biomedicine: Making sense of raw text Irena Spasic, Sophia Ananiadou, John McNaught and Anand Kumar Date received (in revised form): 7th June 2005 Abstract The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically distill information, extract facts, discover implicit links and generate hypotheses relevant to user needs. Ontologies, as conceptual models, provide the necessary framework for semantic representation of textual information. The principal link between text and an ontology is terminology, which maps terms to domain-specific concepts. This paper summarises different approaches in which ontologies have been used for text-mining applications in biomedicine. INTRODUCTION Text is the predominant medium for information exchange among experts. 1 The volume of biomedical literature is increasing at such a rate that it is difficult to efficiently locate, retrieve and manage relevant information without the use of text-mining (TM) applications. In order to share the vast amounts of biomedical knowledge effectively, textual evidence needs to be linked to ontologies as the main repositories of formally represented knowledge. Ontologies are conceptual models that aim to support consistent and unambiguous knowledge sharing and that provide a framework for knowledge integration....
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This note was uploaded on 06/14/2011 for the course DATABASE - taught by Professor - during the Spring '11 term at Aarhus Universitet.
- Spring '11