Special Issue on Information Retrieval, Recommender Systems and Adaptive Systems

Special Issue on Advances in Recommender Systems

Recent advances in electronic media and computer networks have allowed the creation of large and distributed repositories of information. However, the immediate availability of extensive resources for use by broad classes of computer users gives rise to new challenges in everyday life. These challenges arise from the fact that users cannot exploit available resources effectively when the amount...

Context-aware Recommender Systems J.UCS Special Issue

Recommender systems have been researched and deployed extensively over the last decade in various application areas, including e-commerce, technology enhanced learning, e-health, adaptive multimedia and knowledge management. The three approaches of recommender systems commonly implemented are collaborative filtering, content-based filtering and hybrid filtering which combines aspects of both ap...

Introduction to the IEEE Intelligent Systems Special Issue: Recommender Systems

Recommender systems support users in the identification of interesting products and services in situations where the amount and complexity of offers outstrips the capability of a user to survey it and to reach a decision. The interest in recommender systems has dramatically increased owing to the demand for personalization technologies by large, successful ecommerce applications (for example, s...

Benchmarking Adaptive Retrieval and Recommender Systems

In recent years, immense progress has been made in the development of recommendation, retrieval, and personalisation techniques. The evaluation of these systems is still based on traditional information retrieval and statistics metrics, e.g., precision, recall and/or RMSE, often not taking the use-case and situation of the actual system into consideration. However, the rapid evolution of recomm...

Introduction to Special Issue on User-Centred Recommender Systems