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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| Published in: | Knowledge-based systems Vol. 175; pp. 96 - 106 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Amsterdam
Elsevier B.V
01.07.2019
Elsevier Science Ltd |
| Subjects: | |
| ISSN: | 0950-7051, 1872-7409 |
| Online Access: | Get full text |
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