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Iterative Constrained Clustering for Subjectivity Word Sense Disambiguation

Cem Akkaya, Janyce Wiebe, Rada Mihalcea
2014 Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics  
Subjectivity word sense disambiguation (SWSD) is a supervised and applicationspecific word sense disambiguation task disambiguating between subjective and objective senses of a word. Not surprisingly, SWSD suffers from the knowledge acquisition bottleneck. In this work, we use a "cluster and label" strategy to generate labeled data for SWSD semiautomatically. We define a new algorithm called Iterative Constrained Clustering (ICC) to improve the clustering purity and, as a result, the quality of
more » ... ult, the quality of the generated data. Our experiments show that the SWSD classifiers trained on the ICC generated data by requiring only 59% of the labels can achieve the same performance as the classifiers trained on the full dataset.
doi:10.3115/v1/e14-1029 dblp:conf/eacl/AkkayaWM14 fatcat:ss3yefc2qjgrxn3osgln5sir3q