Abstract
In this paper we propose automatic hedge detection methods for Korean. We select sentential contextual features adjusted for Korean, and used supervised machine-learning algorithms to train models to detect hedges in Wikipedia documents. Our SVM-based model achieved an F1-score of 90.8% for Korean.
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Kang, SJ., Jeong, JS., Kang, IS. (2012). Detecting Korean Hedge Sentences in Wikipedia Documents. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_91
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DOI: https://doi.org/10.1007/978-3-642-32645-5_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32644-8
Online ISBN: 978-3-642-32645-5
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