When the number of books provided by library is relatively large, it becomes difficult for user
to select appropriate book from a lot of candidate books. In this case, this paper designs a …

Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …

Recommender systems are programs that aim to provide personalized recommendations to
users for specific items (eg music, books) in online sharing communities or on e-commerce …

Collaborative filtering is a popular recommendation technique, which suggests items to
users by exploiting past user-item interactions involving affinities between pairs of users or …

Recommendation systems are becoming important with the increased availability of online
services. A typical approach used in recommendations is collaborative filtering. However …

Recommender systems (RS) aim to capture the user behavior by suggesting/recommending
users with relevant items or services that they find interesting in. Recommender systems …

In the field of recommendation system, the memory-based Collaborative filtering has been
proven to be useful in lots of practices. Similarity measures like Pearson correlation …

Recommender Systems have been widely used in Information and Communication
Technology (ICT). The main reason for this extensive use is to decrease the problem of …

Various clustering approaches have been widely adopted to improve the accuracy and
scalability of collaborative filtering-based recommender systems as the major objectives …

In order to build relevant, useful, and effective recommender systems, researchers need to
understand why users come to these systems and how users judge recommendation lists …