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dc.contributor.authorPitsilis, Georgios
dc.contributor.authorZhang, Xiangliang
dc.contributor.authorWang, Wei
dc.date.accessioned2015-08-04T06:24:13Z
dc.date.available2015-08-04T06:24:13Z
dc.date.issued2011
dc.identifier.isbn9783642221996
dc.identifier.issn18684238
dc.identifier.doi10.1007/978-3-642-22200-9_9
dc.identifier.urihttp://hdl.handle.net/10754/564340
dc.description.abstractIn this work, we explore the benefits of combining clustering and social trust information for Recommender Systems. We demonstrate the performance advantages of traditional clustering algorithms like k-Means and we explore the use of new ones like Affinity Propagation (AP). Contrary to what has been used before, we investigate possible ways that social-oriented information like explicit trust could be exploited with AP for forming clusters of high quality. We conducted a series of evaluation tests using data from a real Recommender system Epinions.com from which we derived conclusions about the usefulness of trust information in forming clusters of Recommenders. Moreover, from our results we conclude that the potential advantages in using clustering can be enlarged by making use of the information that Social Networks can provide. © 2011 International Federation for Information Processing.
dc.publisherSpringer Nature
dc.subjectAffinity Propagation
dc.subjectClustering
dc.subjectEpinions.com
dc.subjectRecommender Systems
dc.subjectSocial Trust
dc.titleClustering recommenders in collaborative filtering using explicit trust information
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.contributor.departmentMachine Intelligence & kNowledge Engineering Lab
dc.identifier.journalIFIP Advances in Information and Communication Technology
dc.conference.date29 June 2011 through 1 July 2011
dc.conference.name5th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2011
dc.conference.locationCopenhagen
dc.contributor.institutionFaculty of Science, Technology and Communication, Université du Luxembourg, Luxembourg, Luxembourg
dc.contributor.institutionInterdisciplinary Centre for Security, Reliability and Trust, SnT Centre, Université du Luxembourg, Luxembourg, Luxembourg
kaust.personZhang, Xiangliang


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