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dc.contributor.authorAngrosh, M.A.
dc.contributor.authorCranefield, Stephen
dc.contributor.authorStanger, Nigel
dc.date.available2014-08-28T01:33:38Z
dc.date.copyright2013
dc.identifier.citationM. A. Angrosh, Stephen Cranefield and Nigel Stanger (2013). Context identification of sentences in research articles: Towards developing intelligent tools for the research community. Natural Language Engineering, 19, pp 481-515. doi:10.1017/S1351324912000277.en_NZ
dc.identifier.issn1351-3249
dc.identifier.urihttp://hdl.handle.net/10523/4959
dc.descriptionThis is the definitive version of the contribution as published at Cambridge Journals Online.en_NZ
dc.description.abstractScientific literature is an important medium for disseminating scientific knowledge. However, in recent times, a dramatic increase in research output has resulted in challenges for the research community. An increasing need is felt for tools that exploit the full content of an article and provide insightful services with value beyond quantitative measures such as impact factors and citation counts. However, the intricacies of language and thought, and the unstructured format of research articles present challenges in providing such services. The identification of sentence contexts that encode the role of specific sentences in advancing an article's scientific argument can facilitate in developing intelligent tools for the research community. This paper describes our research work in this direction. First, we investigate the possibility of identifying contexts associated with sentences and propose a scheme of thirteen context type definitions for sentences, based on the generic rhetorical pattern found in scientific articles. We then present the results of our experiments using sequential classifiers – conditional random fields – for achieving automatic context identification. We also describe our Semantic Web application developed for providing citation context based information services for the research community. Finally, we present a comparison and analysis of our results with similar studies and explain the distinct features of our application.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoenen_NZ
dc.publisherCambridge University Pressen_NZ
dc.relation.ispartofNatural Language Engineeringen_NZ
dc.relation.urihttp://journals.cambridge.org/action/displayJournal?jid=NLEen_NZ
dc.subjectCitation classificationen_NZ
dc.subjectConditional random fieldsen_NZ
dc.subjectSemantic weben_NZ
dc.titleContext identification of sentences in research articles: Towards developing intelligent tools for the research communityen_NZ
dc.typeJournal Articleen_NZ
dc.date.updated2014-08-27T23:32:07Z
otago.schoolInformation Scienceen_NZ
otago.relation.issue4en_NZ
otago.relation.volume19en_NZ
dc.identifier.doi10.1017/S1351324912000277en_NZ
otago.bitstream.endpage515en_NZ
otago.bitstream.startpage481en_NZ
otago.openaccessOpenen_NZ
dc.rights.statementCopyright © Cambridge University Press 2012en_NZ
dc.description.refereedPeer Revieweden_NZ
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