Recommender Systems: Approaches, Challenges and Applications (Volume III)

Dear Colleagues,

Recommender systems have been applied in several domains (e.g., tourism, health, education, e-commerce, etc.) to help users determine more satisfactory choices. The possibility of formulating personalized recommendations enhances the effectiveness of recommender systems. As such, considering aspects such as user preferences, personality and expectations can improve the quality of recommendations. It is important to study and develop new intelligent strategies allowing a greater awareness of the user or group of users, while considering new ways of evaluating recommendation systems, such as diversity, satisfaction, user experience, coverage, trust, fairness and transparency.

Following the success of Volume I and Volume II of this Special Issue, in Volume III, we continue to assist all those interested in the topic to promote their vision and ideas.

The purpose of this Special Issue is to explore novel artificial intelligence solutions for overcoming the current challenges of recommender systems and to improve the quality of recommendations.

Topics relevant for this Special Issue include:

• Group recommender systems;
• Cross-domain recommendations;
• Context-aware recommender systems;
• Personalized recommendations;
• Recommendations based on machine learning/deep learning;
• Novelty, diversity or serendipity in recommender systems;
• Explanation methods for recommender systems;
• Cognitive and affective aspects in recommender systems (emotions, personality, mood, motivations, etc.);
• Transfer learning in recommender systems.

Dr. Patrícia Alves
Prof. Dr. Goreti Marreiros
Guest Editors

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• recommender systems
• group recommender systems
• cold-start problem
• collaborative filtering
• content-based filtering
• hybrid recommender systems
• machine learning
• deep learning
• reinforcement learning for recommender systems
• affective computing in recommender systems

• Recommender Systems: Approaches, Challenges and Applications in Electronics (11 articles)
• Recommender Systems: Approaches, Challenges and Applications (Volume II) in Electronics (7 articles)