TY - CHAP
T1 - A comparative study of an unsupervised word sense disambiguation approach
AU - Xiong, Wei
AU - Song, Min
AU - DeVersterre, Lori Watrous
N1 - Funding Information:
Financial support from Academy of Finland is gratefully acknowledged (Grant Number 111692). The author would also like to thank Johnny Lindroos, Fredrick Sundell and Marketta Hiisa for their contribution to the project and their assistance in carrying out some of the experiments.
Publisher Copyright:
© 2013, IGI Global.
PY - 2013/3/31
Y1 - 2013/3/31
N2 - Word sense disambiguation is the problem of selecting a sense for a word from a set of predefined possibilities. This is a significant problem in the biomedical domain where a single word may be used to describe a gene, protein, or abbreviation. In this paper, we evaluate SENSATIONAL, a novel unsupervised WSD technique, in comparison with two popular learning algorithms: support vector machines (SVM) and K-means. Based on the accuracy measure, our results show that SENSATIONAL outperforms SVM and K-means by 2% and 17%, respectively. In addition, we develop a polysemy-based search engine and an experimental visualization application that utilizes SENSATIONAL's clustering technique.
AB - Word sense disambiguation is the problem of selecting a sense for a word from a set of predefined possibilities. This is a significant problem in the biomedical domain where a single word may be used to describe a gene, protein, or abbreviation. In this paper, we evaluate SENSATIONAL, a novel unsupervised WSD technique, in comparison with two popular learning algorithms: support vector machines (SVM) and K-means. Based on the accuracy measure, our results show that SENSATIONAL outperforms SVM and K-means by 2% and 17%, respectively. In addition, we develop a polysemy-based search engine and an experimental visualization application that utilizes SENSATIONAL's clustering technique.
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U2 - 10.4018/978-1-4666-3604-0.ch066
DO - 10.4018/978-1-4666-3604-0.ch066
M3 - Chapter
AN - SCOPUS:84944037136
SN - 1466636041
SN - 9781466636040
VL - 3
SP - 1306
EP - 1316
BT - Bioinformatics
PB - IGI Global
ER -