The State of Recommender Systems for E-commerce

Dear Colleagues,

We are inviting submissions to the Special Issue entitled “The State of Recommender Systems for E-commerce”.

The e-commerce industry has been continuously growing since its beginning. It has gained even more popularity during the last two years thanks to restricted access to traditional stores as a result of the pandemic. The choice of goods available online imposes additional effort in finding the right products to suit individual needs. Recommender systems play an important role not only in overcoming the information/product overload problem, but also guiding clients through a store as a personal assistant, helping to build a long-term relationship.

This Special Issue focuses on recommender systems for e-commerce and aims to present advances in machine learning and artificial intelligence in this area. It focuses on a wide range of artificial intelligence applications such as: user profiling and updating; text, image, and review processing; and recommendation engines. Any novel works on the application of artificial intelligence for e-commerce recommender systems are highly welcome.

We invite submissions on all topics of algorithms and theories for e-commerce recommender systems, including:

• Recommender systems for e-commerce;
• User-adaptive profiling;
• User preference change detection and adaptation;
• Context-aware recommender systems;
• Reinforcement learning for recommender systems;
• Fuzzy techniques for recommender systems;
• Transfer learning for recommender systems;
• Deep learning for recommender systems;
• Evaluation of recommender systems;
• Recommendation explainability;
• Adversarial recommender systems;
• Privacy and trust in recommender systems.

Dr. Tomasz Zdziebko
Prof. Dr. Piotr Sulikowski
Guest Editors

Manuscript Submission Information

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