@article{ref1,
title="A combined approach to emotion detection in suicide notes",
journal="Biomedical informatics insights",
year="2012",
author="Pak, Alexander and Bernhard, Delphine and Paroubek, Patrick and Grouin, Cyril",
volume="5",
number="Suppl 1",
pages="105-114",
abstract="In this paper, we present the system we have developed for participating in the second task of the i2b2/VA 2011 challenge dedicated to emotion detection in clinical records. On the official evaluation, we ranked 6th out of 26 participants. Our best configuration, based upon a combination of both a machine-learning based approach and manually-defined transducers, obtained a 0.5383 global F-measure, while the distribution of the other 26 participants' results is characterized by mean = 0.4875, stdev = 0.0742, min = 0.2967, max = 0.6139, and median = 0.5027. Combination of machine learning and transducer is achieved by computing the union of results from both approaches, each using a hierarchy of sentiment specific classifiers.<p /> <p>Language: en</p>",
language="en",
issn="1178-2226",
doi="10.4137/BII.S8969",
url="http://dx.doi.org/10.4137/BII.S8969"
}