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Presentation Bias in movie recommendation algorithms

dc.contributor.advisorPinheiro, Flávio Luís Portas
dc.contributor.advisorAlmeida, Francisco Rosas
dc.contributor.authorGarat, Fernanda Velasco
dc.date.accessioned2021-03-24T16:46:52Z
dc.date.available2021-03-24T16:46:52Z
dc.date.issued2021-03-18
dc.descriptionDissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization Information Analysis and Management
dc.description.abstractThe emergence of video on demand (VOD) has transformed the way the content finds its audience. Several improvements have been made on algorithms to provide better movie recommendations to individuals. Given the huge variety of elements that characterize a film (such as casting, genre, soundtrack, amongst others artistic and technical aspects) and that characterize individuals, most of the improvements relied on accomplishing those characteristics to do a better job regarding matching potential clients to each product. However, little attention has been given to evaluate how the algorithms’ result selection are affected by presentation bias. Understanding bias is key to choosing which algorithms will be used by the companies. The existence of a system with presentation bias and feedback loop is already a problem stated by Netflix. In this sense, this research will fill that gap providing a comparative analysis of the bias of the major movie recommendation algorithms.pt_PT
dc.identifier.tid202682315pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/114353
dc.language.isoengpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectRecommendation systempt_PT
dc.subjectAlgorithmpt_PT
dc.subjectPresentation biaspt_PT
dc.subjectNetflixpt_PT
dc.subjectVideo on demand (VOD)pt_PT
dc.titlePresentation Bias in movie recommendation algorithmspt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Estatística e Gestão de Informação, com especialização em Análise e Gestão de Informaçãopt_PT

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