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Detecting Korean hedge sentences in Wikipedia documents
Abstract In this paper we propose automatic hedge dIn 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. achieved an F1-score of 90.8% for Korean.
Abstractsub In this paper we propose automatic hedge dIn 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. achieved an F1-score of 90.8% for Korean.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-32645-5_91  +
Has author Kang S.-J. + , Jeong J.-S. + , Kang I.-S. +
Has extra keyword Contextual feature + , Detection methods + , Train model + , Wikipedia + , Information technology + , Learning algorithms + , Learning systems + , Websites + , Fences +
Has keyword Korean Hedge Detection + , Machine learning + , Uncertainty Detection +
Isbn 9783642326448  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 730–735  +
Published in Lecture Notes in Computer Science +
Title Detecting Korean hedge sentences in Wikipedia documents +
Type conference paper  +
Volume 7425 LNCS  +
Year 2012 +
Creation dateThis property is a special property in this wiki. 7 November 2014 11:19:02  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 11:19:02  +
DateThis property is a special property in this wiki. 2012  +
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