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Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-27210-3_32
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dc.titleA comparison of classifiers for detecting hedges
dc.contributor.authorKang, S.-J.
dc.contributor.authorKang, I.-S.
dc.contributor.authorNa, S.-H.
dc.date.accessioned2013-07-04T08:09:38Z
dc.date.available2013-07-04T08:09:38Z
dc.date.issued2011
dc.identifier.citationKang, S.-J.,Kang, I.-S.,Na, S.-H. (2011). A comparison of classifiers for detecting hedges. Communications in Computer and Information Science 264 CCIS : 251-257. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-27210-3_32" target="_blank">https://doi.org/10.1007/978-3-642-27210-3_32</a>
dc.identifier.isbn9783642272097
dc.identifier.issn18650929
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40669
dc.description.abstractA hedge is a linguistic device used to avoid using a categorical sentence. Hedges can be used to determine whether a sentence is factual by merely regarding a sentence containing hedges as non-factual. In this paper, we perform a comparative experiment of various classification methods for hedge detection. Among four different classification methods, we observe that SVM shows the best performance and that the SVM-based method finally outperforms the best system in the CoNLL2010-ST task. © 2011 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-27210-3_32
dc.sourceScopus
dc.subjectHedge Detection
dc.subjectInformation Extraction
dc.subjectMachine Learning
dc.subjectNatural Language Processing
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-27210-3_32
dc.description.sourcetitleCommunications in Computer and Information Science
dc.description.volume264 CCIS
dc.description.page251-257
dc.identifier.isiutNOT_IN_WOS
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