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SUMMARY:Acquiring Sense Tagged Examples using Relevance Feedback - Stuart 
 Moore (Computer Laboratory)
DTSTART:20090209T123000Z
DTEND:20090209T133000Z
UID:TALK16802@talks.cam.ac.uk
CONTACT:Diarmuid Ó Séaghdha
DESCRIPTION:At this session of the NLIP Reading Group we'll be discussing 
 the following paper:\n\nMark Stevenson\, Yikun Guo and Robert Gaizauskas. 
 2008. "Acquiring Sense Tagged Examples using Relevance Feedback":http://ww
 w.aclweb.org/anthology-new/C/C08/C08-1102.pdf. In Proceedings of the  22nd
  International Conference on Computational Linguistics (COLING-08).\n\n*Ab
 stract:*\nSupervised approaches to Word Sense Disambiguation (WSD) have be
 en shown to outperform other approaches but are hampered by reliance on la
 beled training examples (the data acquisition bottleneck). This paper pres
 ents a novel approach to the automatic acquisition of labeled examples for
  WSD which makes use of the Information Retrieval technique of relevance f
 eedback. This semi-supervised method generates additional labeled examples
  based on existing annotated data. Our approach is applied to a set of amb
 iguous terms from biomedical journal articles and found to significantly 
 improve the performance of a state-of-the-art WSD system.
LOCATION:GS15\, Computer Laboratory
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