Machine Learning and Artificial Intelligence in Recommender Systems

Dear Colleagues,

Recommender systems play a crucial role in mitigating information overload by providing personalized suggestions in various domains such as e-commerce, entertainment, healthcare, and education. With the rapid advancements in machine learning (ML) and artificial intelligence (AI), modern recommender systems have evolved beyond traditional collaborative filtering and content-based approaches. This Special Issue focuses on cutting-edge research that leverages ML and AI techniques, including deep learning, graph-based methods, reinforcement learning, and contrastive learning, to enhance recommendation accuracy, diversity, and interpretability. Topics of interest include, but are not limited to, graph neural networks (GNNs) for recommendation, intent-aware and adversarial learning-based models, cross-domain recommendations, and responsible AI-driven recommendation frameworks. We welcome original research and review articles that contribute to advancing the theoretical foundations, novel methodologies, and real-world applications of intelligent recommender systems.

Dr. Wei Zhou
Guest Editor

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