Integrating Individual and Aggregate Diversity in Top-N Recommendation

Recommender systems have become one of the main components of web technologies that help people to cope with information overload. Based on the analysis of past user behavior, these systems filter items according to users’ likes and interests. Two of the most important metrics used to analyze the performance of these systems are the accuracy and diversity of the recommendation lists. Whereas all the efforts exerted in the prediction of the user...