The item-based collaborative filtering technique recommends an item to the user from the
rating of k-nearest items. Generally, a random value of k is considered to find nearest …

Top-N item recommendation is one of the important tasks of recommenders. Collaborative
filtering is the most popular approach to building recommender systems which can predict …

Collaborative Filtering (CF), one of the most successful technologies among recommender
systems, is a system assisting users to easily find useful information. One notable challenge …

Recommender systems are widely deployed to provide user purchasing suggestion on
eCommerce websites. The technology that has been adopted by most recommender …

This paper discusses the 3A recommender system that targets CSCL (computersupported
collaborative learning) and CSCW (computer-supported collaborative work) environments …

Purpose–Analyzing current recommender systems, it is observed that the cold start problem
is still too far away to be satisfactorily solved. This paper aims to present a hybrid …

E-commerce companies have developed tools to assist users in finding the most suitable
items for their needs or preferences. The most successful tool in this area has been the …

In collaborative filtering, many neighbors are needed to improve the quality and stability of
the recommendation. The quality may not be good mainly due to the high similarity between …

Because of the serious information overload problem on the internet, the recommender
system as one of the most important solutions has been widely used to help users find more …

Collaborative recommendation (CR) approaches have proven effective for the Top-N
recommendation task. We introduce a novel approach, Rerank-CR, that further improves the …