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dc.contributor.authorKotkov, Denis
dc.contributor.authorVeijalainen, Jari
dc.contributor.authorWang, Shuaiqiang
dc.contributor.editorMajchrzak, Tim A.
dc.contributor.editorTraverso, Paolo
dc.contributor.editorKrempels, Karl-Heinz
dc.contributor.editorMonfort, Valérie
dc.date.accessioned2017-06-14T11:51:52Z
dc.date.available2017-06-14T11:51:52Z
dc.date.issued2017
dc.identifier.citationKotkov, D., Veijalainen, J., & Wang, S. (2017). A Serendipity-Oriented Greedy Algorithm for Recommendations. In T. A. Majchrzak, P. Traverso, K.-H. Krempels, & V. Monfort (Eds.), <i>WEBIST 2017 : Proceedings of the 13rd International conference on web information systems and technologies. Volume 1</i> (pp. 32-40). SCITEPRESS Science And Technology Publications. <a href="https://doi.org/10.5220/0006232800320040" target="_blank">https://doi.org/10.5220/0006232800320040</a>
dc.identifier.otherCONVID_27065316
dc.identifier.otherTUTKAID_74133
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/54494
dc.description.abstractMost recommender systems suggest items to a user that are popular among all users and similar to items the user usually consumes. As a result, a user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected, i.e. serendipitous items. In this paper, we propose a serendipity-oriented algorithm, which improves serendipity through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm and compare it with others, we employ a serendipity metric that captures each component of serendipity, unlike the most common metric.
dc.language.isoeng
dc.publisherSCITEPRESS Science And Technology Publications
dc.relation.ispartofWEBIST 2017 : Proceedings of the 13rd International conference on web information systems and technologies. Volume 1
dc.subject.otherserendipity
dc.subject.othernovelty
dc.subject.otherunexpectedness
dc.titleA Serendipity-Oriented Greedy Algorithm for Recommendations
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201706142857
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2017-06-14T09:15:03Z
dc.relation.isbn978-989-758-246-2
dc.type.coarconference paper
dc.description.reviewstatuspeerReviewed
dc.format.pagerange32-40
dc.type.versionacceptedVersion
dc.rights.copyright© 2017 by SCITEPRESS – Science and Technology Publications, Lda. This is a final draft version of an article whose final and definitive form has been published by SCITEPRESS. Published in this repository with the kind permission of the publisher.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational conference on web information systems and technologies
dc.subject.ysosuosittelujärjestelmät
dc.subject.ysoalgoritmit
jyx.subject.urihttp://www.yso.fi/onto/yso/p28483
jyx.subject.urihttp://www.yso.fi/onto/yso/p14524
dc.relation.doi10.5220/0006232800320040


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