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dc.contributor.authorPortugal, Ivens
dc.contributor.authorAlencar, Paulo
dc.contributor.authorCowan, Donald
dc.date.accessioned2018-01-02 16:53:37 (GMT)
dc.date.available2018-01-02 16:53:37 (GMT)
dc.date.issued2018-05-01
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2017.12.020
dc.identifier.urihttp://hdl.handle.net/10012/12797
dc.descriptionThe final publication is available at Elsevier via https://doi.org/10.1016/j.eswa.2017.12.020 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.description.abstractRecommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. However, choosing a suitable machine learning algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using machine learning algorithms often faces problems and raises questions that must be resolved. This paper presents a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies new research opportunities. The goals of this study are to (i) identify trends in the use or research of machine learning algorithms in recommender systems; (ii) identify open questions in the use or research of machine learning algorithms; and (iii) assist new researchers to position new research activity in this domain appropriately. The results of this study identify existing classes of recommender systems, characterize adopted machine learning approaches, discuss the use of big data technologies, identify types of machine learning algorithms and their application domains, and analyzes both main and alternative performance metrics.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (NSERC) Ontario Research Fund of the Ontario Ministry of Research, Innovation, and Scienceen
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectApplication domainsen
dc.subjectMachine learningen
dc.subjectMachine learning algorithmsen
dc.subjectPerformance metricsen
dc.subjectRecommender systemsen
dc.subjectSystematic review of the literatureen
dc.titleThe use of machine learning algorithms in recommender systems: A systematic reviewen
dc.typeArticleen
dcterms.bibliographicCitationPortugal, I., Alencar, P., & Cowan, D. (2018). The use of machine learning algorithms in recommender systems: A systematic review. Expert Systems with Applications, 97, 205–227. https://doi.org/10.1016/j.eswa.2017.12.020en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2David R. Cheriton School of Computer Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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