Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach

Recommendation systems usually involve exploiting the relations among known features and content that describe items (content-based filtering) or the overlap of similar users who interacted with or rated the target item (collaborative filtering). To combine these two filtering approaches, current mo...

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Veröffentlicht in:Knowledge-based systems Jg. 136; S. 37 - 45
Hauptverfasser: Yang, Shuo, Korayem, Mohammed, AlJadda, Khalifeh, Grainger, Trey, Natarajan, Sriraam
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 15.11.2017
Elsevier Science Ltd
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ISSN:0950-7051, 1872-7409
Online-Zugang:Volltext
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