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: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Amsterdam
Elsevier B.V
15.11.2017
Elsevier Science Ltd |
| Schlagworte: | |
| ISSN: | 0950-7051, 1872-7409 |
| Online-Zugang: | Volltext |
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