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dc.contributor.authorBuitelaar, Paul
dc.contributor.authorBordea, Georgeta
dc.contributor.authorQasemiZadeh, Behrang
dc.date.accessioned2014-06-11T11:55:58Z
dc.date.available2014-06-11T11:55:58Z
dc.date.issued2012
dc.identifier.citationQasemiZadeh, B,Buitelaar, P,Chen, TQ,Bordea, G (2012) Semi-Supervised Technical Term Tagging With Minimal User Feedback LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATIONen_US
dc.identifier.urihttp://hdl.handle.net/10379/4383
dc.description.abstractIn this paper, we address the problem of extracting technical terms automatically from an unannotated corpus. We introduce a technology term tagger, that is based on Liblinear Support Vector Machines and employs linguistic features including Part of Speech tags and Dependency Structures, in addition to user feedback to perform the task of identification of technology related terms. Our experiments show the applicability of our approach as witnessed by acceptable results on precision and recall.en_US
dc.language.isoenen_US
dc.relation.ispartofLREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATIONen
dc.subjectTechnical Term Taggingen_US
dc.subjectInformation Extractionen_US
dc.subjectMachine Learningen_US
dc.titleSemi-Supervised Technical Term Tagging With Minimal User Feedbacken_US
dc.typeConference Paperen_US
dc.date.updated2014-06-05T14:07:19Z
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funder|~|
dc.internal.rssid5623872
dc.local.contactBehrang Qasemizadeh, Deri, Ida Business Park, Lower Dangan, Nui Galway. Email: behrang.qasemizadeh@deri.org
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
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