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Data-driven user profiling to support web adaptation through cognitive styles and navigation behavior

dc.contributor.authorGermanakos, Panagiotisen
dc.contributor.authorPapatheocharous, Efien
dc.contributor.authorBelk, Mariosen
dc.contributor.authorSamaras, George S.en
dc.creatorGermanakos, Panagiotisen
dc.creatorPapatheocharous, Efien
dc.creatorBelk, Mariosen
dc.creatorSamaras, George S.en
dc.date.accessioned2019-11-13T10:40:15Z
dc.date.available2019-11-13T10:40:15Z
dc.date.issued2012
dc.identifier.issn1868-4238
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54026
dc.description.abstractThis paper aims to analyze human navigation behavior and identify similarities of cognitive styles using measures obtained from psychometric tests. Specific navigation metrics are utilized to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with a user study that entails a psychometric-based survey for extracting the users' cognitive styles, combined with a real usage scenario of users navigating in a controlled Web environment. A total of 84 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for assisting adaptive interactive systems to organize and present information and functionalities in an adaptive format to diverse user groups. © 2012 IFIP International Federation for Information Processing.en
dc.source8th International Workshop on Artificial Intelligence Applications and Innovations, AIAI 2012: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMBen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84870930346&doi=10.1007%2f978-3-642-33412-2_51&partnerID=40&md5=0ecdbf8816881b4dbbae86731e0743cb
dc.subjectBehavioral researchen
dc.subjectArtificial intelligenceen
dc.subjectHuman behaviorsen
dc.subjectUsage scenariosen
dc.subjectNavigationen
dc.subjectUser studyen
dc.subjectCognitive Stylesen
dc.subjectAdaptive interactive systemsen
dc.subjectPsychometric testen
dc.subjectNavigation behavioren
dc.subjectNavigation patternsen
dc.subjectWeb environmenten
dc.subjectData-driven Profiling/Personalizationen
dc.subjectHuman Behavioren
dc.subjectHuman navigationen
dc.subjectUser groupsen
dc.subjectUser profilingen
dc.subjectWeb adaptationen
dc.subjectWeb Miningen
dc.titleData-driven user profiling to support web adaptation through cognitive styles and navigation behavioren
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1007/978-3-642-33412-2_51
dc.description.volume382 AICTen
dc.description.issuePART 2en
dc.description.startingpage500
dc.description.endingpage509
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Conference code: 94333en
dc.description.notesCited By :2</p>en
dc.source.abbreviationIFIP Advances in Information and Communication Technologyen
dc.contributor.orcidBelk, Marios [0000-0001-6200-0178]
dc.contributor.orcidPapatheocharous, Efi [0000-0002-5157-8131]
dc.gnosis.orcid0000-0001-6200-0178
dc.gnosis.orcid0000-0002-5157-8131


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