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- W2492374649 abstract "Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeINFORMS TutORials in Operations ResearchState-of-the-Art Decision-Making Tools in the Information-Intensive Age Personalization and Recommender SystemsGediminas Adomavicius, Zan Huang, Alexander TuzhilinGediminas Adomavicius, Zan Huang, Alexander TuzhilinPublished Online:14 Oct 2014https://doi.org/10.1287/educ.1080.0044Abstract In this tutorial, we present an overview of the personalization field and review different types of personalization. We also discuss the general personalization process and position the field of recommender systems as an integral part of this process. We review the field of recommender systems by describing a number of “traditional” recommendation approaches and their extensions. Finally, we discuss several future research directions for personalization and recommender systems, including integrated personalization process, data acquisition for recommender systems, advanced modeling of user preferences, other model-based techniques for recommendation, evaluation of recommender systems, recommendation flexibility and scalability, and trust and privacy issues in recommender systems. This publication has no references to display. Previous Back to Top Next FiguresReferencesRelatedInformation State-of-the-Art Decision-Making Tools in the Information-Intensive AgeSeptember 2008 Article Information Metrics Downloaded 366 times in the past 12 months Information Published Online:October 14, 2014 Copyright © 2008, INFORMSCite asGediminas AdomaviciusZan HuangAlexander Tuzhilin (2014) Personalization and Recommender Systems. INFORMS TutORials in Operations Research null(null):55-107. https://doi.org/10.1287/educ.1080.0044Keywordspersonalizationrecommender systemsalgorithmsPDF download" @default.
- W2492374649 created "2016-08-23" @default.
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- W2492374649 date "2008-09-01" @default.
- W2492374649 modified "2023-09-26" @default.
- W2492374649 title "Personalization and Recommender Systems" @default.
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