Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …

These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …

Recommender systems (RSs) are software tools and techniques that provide suggestions
for items that are most likely of interest to a particular user. In this introductory chapter, we …

In the era of big data, recommender system (RS) has become an effective information
filtering tool that alleviates information overload for Web users. Collaborative filtering (CF) …

In the literature, various collaborative filtering approaches have been developed to perform
an efficient recommendation on top of reducing the search cost of the customers. The …

In recent years there has been an enormous increase in learning resources available online
through massive open online courses and learning management systems. In this context …

Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …

Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …

Artificial neural networks (ANNs), which represent computational models simulating the
biological neural systems, have become a dominant paradigm for solving complex analytical …

With the increasing amount of information on the internet, recommendation system (RS) has
been utilized in a variety of fields as an efficient tool to overcome information overload. In …