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dc.contributor.authorAdomavicius G
dc.contributor.authorMobasher B
dc.contributor.authorRicci F
dc.contributor.authorTuzhilin A
dc.contributor.editor
dc.date.accessioned2020-06-30T09:22:30Z
dc.date.available2020-06-30T09:22:30Z
dc.date.issued2011
dc.identifier.issn0738-4602
dc.identifier.urihttp://dx.doi.org/10.1609/aimag.v32i3.2364
dc.identifier.urihttps://aaai.org/ojs/index.php/aimagazine/article/view/2364
dc.identifier.urihttps://bia.unibz.it/handle/10863/14450
dc.description.abstractContext-aware recommender systems (CARS) generate more.relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches riff incorporating contextual information in the recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and figure research directions for context-aware recommender systems.en_US
dc.languageEnglish
dc.language.isoenen_US
dc.relation
dc.rights
dc.titleContext-aware recommender systemsen_US
dc.typeArticleen_US
dc.date.updated2020-06-30T03:00:41Z
dc.publication.title
dc.language.isiEN-GB
dc.journal.titleAI Magazine
dc.description.fulltextnoneen_US


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