This paper proposes a matrix-based collaborative filtering (CF) employing personal values
(MCFPV). Introduction of various factors such as diversity and long-tailedness in addition to …

Recommender system plays an increasingly important role in identifying the individual's
preference and accordingly makes a personalized recommendation. Matrix factorization is …

Matrix Factorization (MF) is one of the most popular techniques used in Collaborative
Filtering (CF) based Recommender System (RS). Most of the MF methods tend to remove …

Collaborative filtering (CF) approach is successfully applied in the rating prediction of
personal recommendation. But individual information source is leveraged in many of them …

In designing modern recommender systems, item feature information (or side information) is
often ignored as most models focus on exploiting rating information. However, the side …

Recommender systems are widely employed in many fields to recommend products,
services and information to potential customers. As the most successful approach to …

Collaborative Filtering method using latent factor model is one of the most popular
approaches in personal recommending system. It is famous for its good performance by …

Collaborative filtering (CF) has been a very successful approach for building recommender
system, but its widespread use has exposed to some well-known problems including …

Collaborative filtering (CF) has been a very successful approach for building recommender
system, but its widespread use has exposed to some well-known problems including …

Collaborative Filtering is the most widely used prediction technique in Recommendation
System. Most of the current CF recommender systems maintains single criteria user rating in …