User interest dynamics on personalized recommendation

Four real recommender system datasets, the Netflix, SMovieLens, LMovieLens and RYM datasets, are analyzed to gain an insight into their user interest characteristics. A preference of active users to cold objects and a diverse interest of inactive users are revealed, which characteristics are introduced to improve the personalized recommendation algorithms. Based on seven different algorithms, we propose a general improvement formula for them,...