We are performing the digital transition of industry, living the 4th industrial revolution,
building a new World in which the digital, physical and human dimensions are interrelated in …

In recent years, there has been significant growth in the use of online learning resources by
learners. However, due to information overload, many learners are experiencing difficulties …

Due to the explosion of available information on the Internet, the need for effective means of
accessing and processing them has become vital for everyone. Recommender systems …

The rapid evolution of the Internet has resulted in the availability of huge volumes of online
learning resources on the web. However, many learners encounter difficulties in retrieval of …

The recommender systems are recently becoming more significant in the age of rapid
development of the Internet technology due to their ability in making a decision to users on …

Matrix Factorization is a successful approach for generating an effective recommender
system. However, most existing matrix factorization methods suffer from the sparsity and cold …

An e-learning recommender system (RS) aims to generate personalized recommendations
based on learner preferences and goals. The existing RSs in the e-learning domain still …

Traditional Collaborative filtering (CF) is one of the techniques of recommender systems that
has been successfully exploited in various applications, but sometimes they fail to provide …

With the abundance of information produced by users on items (eg, purchase or rating
histories), recommender systems are a major ingredient of online systems such as e-stores …

Among widely used recommendation methods, singular value decomposition (SVD) based
approaches are the most successful ones. Although SVD-based methods are effective, they …