Many of the recent algorithms have been developed to improve the various aspects of
collaborative filtering recommender systems, however, most of them do not take the …

Collaborative filtering (CF) technique has been proved to be one of the most successful
techniques in recommender systems. Two types of algorithms for collaborative filtering have …

Collaborative filtering recommendation algorithm is one of the most successful technologies
for building recommender systems. However, a user–based collaborative filtering method …

Collaborative filtering is one of the most important technologies in e-commerce
recommendation system. Traditional similarity measure methods work poorly when the user …

Collaborative filtering is one of most important technologies in the field of recommender
systems, the process of making predictions about user preferences for products or services …

Collaborative filtering is the most successful recommender system technology to date. It has
been shown to produce high quality recommendations, but the performance degrades with …

Collaborative filtering (CF) is a popular technique for rating prediction in recommender
systems. CF tries to predict the user's rating on an unseen item based on other similar users' …

In recent years most of personalized recommender systems in electronic commerce utilize
collaborative filtering algorithm in order to recommend more appropriate items. User-based …

As one of the most popular recommender technologies, Collaborative Filtering (CF) has
been widely deployed in industry due to its simplicity and interpretability. However, it is …

The aim of recommender systems is to help users to find items that they should be interested
in from over-load information by analyzing historical information about the users to establish …