Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6467
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dc.contributor.authorBasharat, Amna-
dc.contributor.authorArpınar, İ. Budak-
dc.contributor.authorDastgheib, Shima-
dc.contributor.authorKurşuncu, Uğur-
dc.contributor.authorKochut, Krys-
dc.contributor.authorDoğdu, Erdoğan-
dc.date.accessioned2021-09-11T15:36:42Z-
dc.date.available2021-09-11T15:36:42Z-
dc.date.issued2014en_US
dc.identifier.citation8th IEEE International Conference on Semantic Computing -- JUN 16-18, 2014 -- Newport Beach, CAen_US
dc.identifier.isbn978-1-4799-4003-5-
dc.identifier.issn2325-6516-
dc.identifier.urihttps://doi.org/10.1109/ICSC.2014.14-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6467-
dc.description.abstractCrowdsourcing is an emerging paradigm to exploit the notion of human-computation for solving various computational problems, which cannot be accurately solved solely by the machine-based solutions. We use crowdsourcing for large-scale link management in the Semantic Web. More specifically, we develop CrowdLink, which utilizes crowdworkers for verification and creation of triples in Linking Open Data (LOD). LOD incorporates the core data sets in the Semantic Web, yet is not in full conformance with the guidelines for publishing high quality linked data on the Web. Our approach can help in enriching and improving quality of mission-critical links in LOD. Scalable LOD link management requires a hybrid approach, where human intelligent and machine intelligent tasks interleave in a workflow execution. Likewise, many other crowdsourcing applications require a sophisticated workflow specification not only on human intelligent tasks, but also machine intelligent tasks to handle data and control-flow, which is strictly deficient in the existing crowdsourcing platforms. Hence, we are strongly motivated to investigate the interplay of crowdsourcing, and semantically enriched workflows as well as human-machine cooperation in task completion. We demonstrate usefulness of our approach through various link creation and verification tasks, and workflows using Amazon Mechanical Turk. Experimental evaluation demonstrates promising results in terms of accuracy of the links created, and verified by the crowdworkersen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 IEEE International Conference On Semantic Computing (Icsc)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCrowdsourcingen_US
dc.subjectSemantic Weben_US
dc.subjectWorkflow Managementen_US
dc.subjectLinking Open Data (LOD)en_US
dc.subjectHuman Intelligent Tasken_US
dc.subjectOntology Verification and Entity Disambiguationen_US
dc.titleCrowdlink: Crowdsourcing for Large-Scale Linked Data Managementen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesIEEE International Conference on Semantic Computingen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage227en_US
dc.identifier.endpage234en_US
dc.authorid0000-0001-5987-0164-
dc.identifier.wosWOS:000346176100036en_US
dc.identifier.scopus2-s2.0-84906971647en_US
dc.institutionauthorDoğdu, Erdoğan-
dc.identifier.doi10.1109/ICSC.2014.14-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference8th IEEE International Conference on Semantic Computingen_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:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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