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dc.contributor.advisorChairperson, Graduate Committee: John Shepparden
dc.contributor.authorHamilton, Andrew Johnsonen
dc.date.accessioned2013-06-25T18:43:04Z
dc.date.available2013-06-25T18:43:04Z
dc.date.issued2011en
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/1416en
dc.description.abstractTrust propagation in social networks is a challenging task. It is difficult to model human trust, and the data is huge and very sparse. Due to these challenges, the algorithms available to propagate trust have complexity issues. We used the MRFTrust algorithm created by Tosun and Sheppard to produce an anytime algorithm for trust propagation. To do this we use sampling techniques and increased horizon size to reduce the complexity and decrease runtimes. We show that we can dramatically reduce the number of nodes considered in the algorithm, yet still achieve a superior result.en
dc.language.isoenen
dc.publisherMontana State University - Bozeman, College of Engineeringen
dc.subject.lcshSocial networksen
dc.subject.lcshTrusten
dc.titleAn anytime algorithm for trust propagation in social networksen
dc.typeProfessional Paperen
dc.rights.holderCopyright 2011 by Andrew Johnson Hamiltonen
thesis.catalog.ckey1975261en
thesis.degree.committeemembersMembers, Graduate Committee: Rockford J. Ross; Rafal A. Angryken
thesis.degree.departmentComputer Science.en
thesis.degree.genreProfessional Paperen
thesis.degree.nameMSen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage48en


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