Recommender systems (RS) are found in many online applications where users are
exposed to huge sets of items. The goal of recommender systems is to provide the users …

Collaborative Filtering Recommender Systems are one of the most used and well-known
tools in the e-commerce area because they are adaptive and they do not need information …

Recommender systems play an important role in dealing with the problems caused by the
great and growing amount of information, and the collaborative filtering method can propose …

In this paper, we investigate the social-based recommendation algorithms on
heterogeneous social networks and proposed Hete-CF, a social collaborative filtering …

The neighbor selection that determines which users are exploited to estimate a target user's
ratings has an important influence on the accuracy of recommendations of collaborative …

Predicting people who other people may like has recently become an important task in many
online social networks. Traditional collaborative filtering (CF) approaches are popular in …

Advent of the Social Web and the ever increasing popularity of Web 2.0 applications, has led
to a massive amount of information. Therefore, users have difficulties in finding their desired …

Classic collaborative filtering methods suffer from lack of accuracy when it comes to todays
complicated ecommerce websites. Recommender systems can be more efficient and …

This paper proposes a new approach of mentor selection in memory-based collaborative
filtering when no rating is available. Users are represented under the form of a social …

Current available recommender systems mostly predict the target user's preferences using
the traditional method, Collaborative Filtering (CF), which relies on people who share similar …