Εμφάνιση απλής εγγραφής

dc.creatorHaralabopoulos G., Anagnostopoulos I., Zeadally S.en
dc.date.accessioned2023-01-31T08:27:51Z
dc.date.available2023-01-31T08:27:51Z
dc.date.issued2016
dc.identifier10.1145/2899003
dc.identifier.issn19361955
dc.identifier.urihttp://hdl.handle.net/11615/73896
dc.description.abstractIn every environment of information exchange, Information Quality (IQ) is considered one of the most important issues. Studies in Online Social Networks (OSNs) analyze a number of related subjects that span both theoretical and practical aspects, from data quality identification and simple attribute classification to quality assessment models for various social environments. Among several factors that affect information quality in online social networks is the credibility of user-generated content. To address this challenge, some proposed solutions include community-based evaluation and labeling of user-generated content in terms of accuracy, clarity, and timeliness, along with well-established real-time data mining techniques. © 2016 ACM.en
dc.language.isoenen
dc.sourceJournal of Data and Information Qualityen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84983648179&doi=10.1145%2f2899003&partnerID=40&md5=707fbc54a88507a711304c594f02ded8
dc.subjectData miningen
dc.subjectCredibilityen
dc.subjectInformation exchangesen
dc.subjectInformation qualityen
dc.subjectOn-line social networksen
dc.subjectOnline social networks (OSNs)en
dc.subjectQuality assessment modelen
dc.subjectReal-time data miningen
dc.subjectUser-generated contenten
dc.subjectSocial networking (online)en
dc.subjectAssociation for Computing Machineryen
dc.titleThe challenge of improving credibility of user-generated content in online social networksen
dc.typejournalArticleen


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Εμφάνιση απλής εγγραφής