Ontology-Based MEDLINE Document Classification
Camous, Fabrice and Blott, Stephen and Smeaton, Alan F. (2007) Ontology-Based MEDLINE Document Classification. In: BIRD 2007 - 1st International Conference on Bioinformatics Research and Development, 12-14 March 2007, Berlin, Germany. ISBN 978-3-540-71232-9
Full text available as:
An increasing and overwhelming amount of biomedical information is available in the research literature mainly in the form of free-text. Biologists need tools that automate their information search and deal with the high volume and ambiguity of free-text. Ontologies can help automatic information processing by providing standard concepts and information about the relationships between concepts. The Medical Subject Headings (MeSH) ontology is already available and used by MEDLINE indexers to annotate the conceptual content of biomedical articles. This paper presents a domain-independent method that uses the MeSH ontology inter-concept relationships to extend the existing MeSH-based representation of MEDLINE documents. The extension method is evaluated within a document triage task organized by the Genomics track of the 2005 Text REtrieval Conference (TREC). Our method for extending the representation of documents leads to an improvement of 17% over a non-extended baseline in terms of normalized utility, the metric defined for the task. The SVMlight software is used to classify documents.
Archive Staff Only: edit this record