Group recommender systems aim to suggest appropriate products/services to a group of
users rather than individuals. These recommendations rely solely on determining group …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions of relevant items to users. These systems have received increasing attention …

Group recommender systems are becoming very popular in the social web owing to their
ability to provide a set of recommendations to a group of users. Several group recommender …

Recommender systems are increasingly used in various domains like movies, travel, music,
etc. The rise in social activities has increased the usage of recommender systems in general …

Popularity bias is an undesirable phenomenon associated with recommendation algorithms
where popular items tend to be suggested over long-tail ones, even if the latter would be of …

With the rapid advancement of information and communication technologies, e-learning has
gained a considerable attention in recent years. Many researchers have attempted to …

This research aims to empirically examine the stimulators that influence consumers'
behavioral intention to use (IU) mobile entertainment (ME) in Malaysia. The proposed …

Group recommender systems have been designed which, instead of suggesting one or
more items to people individually, concurrently recommend them to a group of people who …

Memory-based collaborating filtering techniques are widely used in recommender systems.
They are based on full initial ratings in a user-item matrix. However, most of the time in group …