Providing recommendations to users in every facet of technology is of prior importance for all
online and offline web platforms. There are several types of recommender systems, like …

Recently, due to the increasing amount of data on the Internet along with the increase in
products' purchasing via e-commerce websites, Recommender Systems (RS) play an …

Recommender Systems are used for finding the needle in the haystack. Recommender
systems are of one the innovations in this revolution, which addresses the problem of …

With the huge amount of information available on the Internet, recommendation systems
gained popularity over the years. Traditional recommendation algorithm usually uses …

Recommender systems use the concept of data analysis and knowledge discovery to
essentially provide personalized recommendations on the web. A number of different …

Owing to the enormous growth in information over the past few decades, the world has
become a global village. The recommendation system remains the most widely used type of …

Recommender systems are often based on collaborative filtering. Previous researches on
collaborative filtering mainly focus on one single recommender or formulating hybrid with …

Content-based and collaborative filtering methods are the most successful solutions in
recommender systems. Content based method is based on items attributes. This method …

Recommender Systems deal with the issue of overloading information by retrieving the most
relevant sources in the wide range of web services. They help users by predicting their …

Due to information explosion, huge number of items are present over web which makes it
difficult for user to find appropriate item from available set of options. Recommender System …