Using topic models to interpret MEDLINE's medical subject headings

Newman, D, Karimi, S and Cavedon, L 2009, 'Using topic models to interpret MEDLINE's medical subject headings', in Ann Nicholson, Xiaodong Li (ed.) AI 2009: Advances in Artificial Intelligence: 22nd Australasian Joint Conference, Melbourne, Australia, December 1-4, 2009. Proceedings, Melbourne, Australia, 1-4 Dec 2009, pp. 270-279.


Document type: Conference Paper
Collection: Conference Papers

Title Using topic models to interpret MEDLINE's medical subject headings
Author(s) Newman, D
Karimi, S
Cavedon, L
Year 2009
Conference name AI 2009: Advances in Artificial Intelligence
Conference location Melbourne, Australia
Conference dates 1-4 Dec 2009
Proceedings title AI 2009: Advances in Artificial Intelligence: 22nd Australasian Joint Conference, Melbourne, Australia, December 1-4, 2009. Proceedings
Editor(s) Ann Nicholson, Xiaodong Li
Publisher Springer
Place of publication Berlin, Germany
Start page 270
End page 279
Abstract We consider the task of interpreting and understanding a taxonomy of classification terms applied to documents in a collection. In particular, we show how unsupervised topic models are useful for interpreting and understanding MeSH, the Medical Subject Headings applied to articles in MEDLINE. We introduce the resampled author model, which captures some of the advantages of both the topic model and the author-topic model. We demonstrate how topic models complement and add to the information conveyed in a traditional listing and description of a subject heading hierarchy.
Subjects Natural Language Processing
Information Systems Organisation
Copyright notice © Springer-Verlag Berlin Heidelberg 2009
ISBN 9783642104381
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