The rise of e-commerce has not only given consumers more choice but has also caused
information overload. In order to quickly find favorite items from vast resources, users are …

Recommender systems (RSs) provide personalized information by learning user
preferences. User-based collaborative filtering (UBCF) is a significant technique widely …

User-based collaborative filtering (UBCF) is widely used in recommender systems (RSs) as
one of the most successful approaches, but traditional UBCF cannot provide …

Recommender systems (RS) analyze user rating information and recommend items that may
interest users. Item-based collaborative filtering (IBCF) is widely used in RSs. However …

This chapter concerns Recommender systems (RSs), providing personalized information by
learning user preferences. User-based collaborative filtering (UBCF) is a significant …

Covering based rough set, an extension of the traditional rough set theory, which uses the
cover set of the universe set instead of the partition of the universe, has proven to be both …

Microblog is different from traditional social networks and e-commerce website for its low
user activity, data sparsity and dynamic of users' preference. So traditional recommendation …

Recommendation systems have become an integral part of our daily lives, providing
personalized information and content tailored to individual preferences. Collaborative …

Item-based collaborative filtering (IBCF) is an important technology that is widely used in
recommender system. It uses historical information to compute item-item similarity and make …