Collaborative Ranking with Social Relationships for Top-N Recommendations
Author:
Affiliation:
1. Aristotle University of Thessaloniki, Thessaloniki, Greece
2. Università della Svizzera italiana (USI), Lugano, Switzerland
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2911451.2914711
Reference14 articles.
1. A Probabilistic Model for Using Social Networks in Personalized Item Recommendation
2. Collaborative Ranking with a Push at the Top
3. Matrix Factorization with Explicit Trust and Distrust Side Information for Improved Social Recommendation
4. Low-rank matrix completion using alternating minimization
5. Matrix Factorization Techniques for Recommender Systems
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