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Biomedical Informatics Insights

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Labeling Emotions in Suicide Notes: Cost-Sensitive Learning with Heterogeneous Features

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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

Abstract

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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