A New Hybrid-Enhanced Recommender System for Mitigating Cold Start Issues
Author:
Affiliation:
1. AMIPS Research Team - EMI, Mohammed V University, Rabat, Morocco
2. SPM Research Team - ENSIAS, Mohammed V University, Rabat, Morocco
3. LTIM - FSBM, Hassan II University, Casablanca, Morocco
Publisher
ACM
Reference18 articles.
1. Using collaborative filtering to weave an information tapestry
2. Recommender systems survey
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2. SNDAE: Self-Normalizing Deep AutoEncoder for Recommendation;Proceedings of the 6th International Conference on Big Data and Internet of Things;2023
3. Recommendation System Issues, Approaches and Challenges Based on User Reviews;Journal of Web Engineering;2022-04-16
4. A Systematic Literature Review on the Hybrid Approaches for Recommender Systems;Computación y Sistemas;2022-03-30
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