Presentation Bias in movie recommendation algorithms

Detalhes bibliográficos
Autor(a) principal: Garat, Fernanda Velasco
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/114353
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization Information Analysis and Management
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spelling Presentation Bias in movie recommendation algorithmsRecommendation systemAlgorithmPresentation biasNetflixVideo on demand (VOD)Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization Information Analysis and ManagementThe 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.Pinheiro, Flávio Luís PortasAlmeida, Francisco RosasRUNGarat, Fernanda Velasco2021-03-24T16:46:52Z2021-03-182021-03-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/114353TID:202682315enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:57:02Zoai:run.unl.pt:10362/114353Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:42:30.576766Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Presentation Bias in movie recommendation algorithms
title Presentation Bias in movie recommendation algorithms
spellingShingle Presentation Bias in movie recommendation algorithms
Garat, Fernanda Velasco
Recommendation system
Algorithm
Presentation bias
Netflix
Video on demand (VOD)
title_short Presentation Bias in movie recommendation algorithms
title_full Presentation Bias in movie recommendation algorithms
title_fullStr Presentation Bias in movie recommendation algorithms
title_full_unstemmed Presentation Bias in movie recommendation algorithms
title_sort Presentation Bias in movie recommendation algorithms
author Garat, Fernanda Velasco
author_facet Garat, Fernanda Velasco
author_role author
dc.contributor.none.fl_str_mv Pinheiro, Flávio Luís Portas
Almeida, Francisco Rosas
RUN
dc.contributor.author.fl_str_mv Garat, Fernanda Velasco
dc.subject.por.fl_str_mv Recommendation system
Algorithm
Presentation bias
Netflix
Video on demand (VOD)
topic Recommendation system
Algorithm
Presentation bias
Netflix
Video on demand (VOD)
description Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization Information Analysis and Management
publishDate 2021
dc.date.none.fl_str_mv 2021-03-24T16:46:52Z
2021-03-18
2021-03-18T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/114353
TID:202682315
url http://hdl.handle.net/10362/114353
identifier_str_mv TID:202682315
dc.language.iso.fl_str_mv eng
language eng
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