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Corpus-based Subtopic Segmentation Using Concept Segment Method

dc.citation.epage975en_US
dc.citation.issue3Ben_US
dc.citation.volume13en_US
dc.citation.woscount0
dc.contributor.authorChang, Tao-Hsingen_US
dc.contributor.authorLee, Chia-Hoangen_US
dc.contributor.authorTam, Hak-Pingen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:23:44Z
dc.date.available2014-12-08T15:23:44Z
dc.date.issued2010-05-01en_US
dc.description.abstractMany studies on topic segmentation have been launched in the past, but these previous methods performed poorly on domain-specific short texts. This paper will propose a method which employs high-level concepts on concept hierarchy to predict the number and location of subtopics in a short text, and then determine the boundary between subtopics using similarity measures. Experimental results show that the proposed method can greatly increase the accuracy of subtopic segmentation for domain-specific short texts.en_US
dc.identifier.issn1343-4500en_US
dc.identifier.journalINFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNALen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/16551
dc.identifier.wosnumberWOS:000208374100017
dc.language.isoen_USen_US
dc.subjectSubtopic segmentationen_US
dc.subjectSubtopic positioningen_US
dc.subjectConceptual segmenten_US
dc.titleCorpus-based Subtopic Segmentation Using Concept Segment Methoden_US
dc.typeArticleen_US

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