Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7489
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dc.contributor.authorÇelikyılmaz, Aslı-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.date.accessioned2021-09-11T15:57:21Z-
dc.date.available2021-09-11T15:57:21Z-
dc.date.issued2009en_US
dc.identifier.citationJoint World Congress of International-Fuzzy-Systems-Association (IFSA)/European Conference of European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT) -- JUL 20-24, 2009 -- Lisbon, PORTUGALen_US
dc.identifier.isbn978-989-95079-6-8-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/7489-
dc.description.abstractGraph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. They rely on graphs that jointly represent each data point. The problem of how to best formulate the graph representation remains an open research topic. In this paper, we introduce a type-2 fuzzy arithmetic to characterize the edge weights of a formed graph as type-2 fuzzy numbers. The fuzzy numbers are identified by the changing parameters of the fuzzy kernel nearest neighbor algorithm, namely the degree of fuzziness and the hyper-parameter of the Gaussian kernel function, both of which have an effect on the uncertainty in forming the affinity matrix of the graph. We introduce a new graph-based semi-supervised learning with the type-2 arithmetic operations. We apply this technique in the framework of label propagation and evaluate on a question answering task. We demonstrate that the type-2 SSL can improve the prediction accuracy and can be considered to be the an alternative tool for text mining applications of computational linguistics.en_US
dc.description.sponsorshipInt Fuzzy Syst Assoc (IFSA), European Soc Fuzzy Log & Technol (EUSFLAT)en_US
dc.language.isoenen_US
dc.publisherEuropean Soc Fuzzy Logic & Technologyen_US
dc.relation.ispartofProceedings of The Joint 2009 International Fuzzy Systems Association World Congress And 2009 European Society of Fuzzy Logic And Technology Conferenceen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGraph-based semi-supervised learningen_US
dc.subjectkernel fuzzy k-nearest neighboren_US
dc.subjecttype-2 fuzzy numbersen_US
dc.titleSpectral Learning With Type-2 Fuzzy Numbers for Question/Answering Systemen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.startpage1388en_US
dc.identifier.endpage1393en_US
dc.identifier.wosWOS:000279170600242en_US
dc.identifier.scopus2-s2.0-84871911276en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conferenceJoint World Congress of International-Fuzzy-Systems-Association (IFSA)/European Conference of European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT)en_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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