A Novel K-medoids clustering recommendation algorithm based on probability distribution for collaborative filtering

Data sparsity is a widespread problem of collaborative filtering (CF) recommendation algorithms. However, some common CF methods cannot adequately utilize all user rating information; they are only able to use a small part of the rating data, depending on the co-rated items, which leads to low predi...

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Veröffentlicht in:Knowledge-based systems Jg. 175; S. 96 - 106
Hauptverfasser: Deng, Jiangzhou, Guo, Junpeng, Wang, Yong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.07.2019
Elsevier Science Ltd
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ISSN:0950-7051, 1872-7409
Online-Zugang:Volltext
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