Collaborative filtering (CF), one of the most widely employed methodologies for
recommender systems, has drawn undeniable attention due to its effectiveness and …

This article proposes a new method to overcome the sparse data problem of the
collaborative filtering models (CF models) by considering the homologous relationship …

In the neighborhood-based Collaborative Filtering (CF) algorithms, the user similarity has an
important effect on the result of CF. In order to evaluate the user similarity comprehensively …

Thanks to its successful application in recommendation systems, collaborative filtering (CF)
technique has become one of the most popular research topic in data mining and …

In recent years, collaborative filtering (CF) techniques have become one of the most
popularly used techniques for providing personalized services to users. CF techniques …

Collaborative Filtering (CF) approaches have been widely used in various applications of
recommender systems. These methods are based on estimating the similarity between …

Memory-based methods for collaborative filtering predict new ratings by averaging
(weighted) ratings between, respectively, pairs of similar users or items. In practice, a large …

Collaborative filtering (CF) is the most popular approach in personalized recommender
systems. Although CF approaches have successfully been used and have the advantage in …

Collaborative filtering (CF) based recommendation system, which can automatically predict
unknown preference of a user to certain products and then generate meaningful …

As one of the collaborative filtering (CF) techniques, memory-based CF technique which
recommends items to users based on rating information of like-minded users (called …