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http://dx.doi.org/10.4218/etrij.16.0115.0896

Korean Coreference Resolution with Guided Mention Pair Model Using Deep Learning  

Park, Cheoneum (Department of Computer Science, Kangwon National University)
Choi, Kyoung-Ho (Department of Computer Science, Kangwon National University)
Lee, Changki (Department of Computer Science, Kangwon National University)
Lim, Soojong (SW & Content Research Laboratory, ETRI)
Publication Information
ETRI Journal / v.38, no.6, 2016 , pp. 1207-1217 More about this Journal
Abstract
The general method of machine learning has encountered disadvantages in terms of the significant amount of time and effort required for feature extraction and engineering in natural language processing. However, in recent years, these disadvantages have been solved using deep learning. In this paper, we propose a mention pair (MP) model using deep learning, and a system that combines both rule-based and deep learning-based systems using a guided MP as a coreference resolution, which is an information extraction technique. Our experiment results confirm that the proposed deep-learning based coreference resolution system achieves a better level of performance than rule- and statistics-based systems applied separately
Keywords
Coreference resolution; Guide mention pair; Multi-pass sieve; Mention pair; Deep learning;
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Times Cited By KSCI : 2  (Citation Analysis)
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