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Publication Date: 30 Jan 2012
Type: Original Research
Journal: Biomedical Informatics Insights
Citation: Biomedical Informatics Insights 2012:5 (Suppl. 1) 99-103
doi: 10.4137/BII.S8930
This paper describes a system developed for Track 2 of the 2011 Medical NLP Challenge on identifying emotions in suicide notes. Our approach involves learning a collection of one-versus-all classifiers, each deciding whether or not a particular label should be assigned to a given sentence. We explore a variety of features types—syntactic, semantic and surface-oriented. Cost-sensitive learning is used for dealing with the issue of class imbalance in the data.
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