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 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 …

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 …

The recommender system's objective is to recommend items to users. Providing
personalized suggestions to users is a challenging task. The traditional recommendation …

With the development and popularity of social networks, an increasing number of consumers
prefer to order tourism products online, and like to share their experiences on social …

The goal of a group recommendation involves providing appropriate information for all
members in a group. Most extant studies use aggregation methods to determine group …

Recommender systems provide personalized content from various choices by mining users'
past preferences. Recommendation helps to overcome the information overload problem as …

Recommender systems provide personalized suggestions to users regarding products and
services. These recommendations are generated for individual users only. However, group …

Recommender Systems have gained popularity in recent years due to their ability to
expedite users' selection processes quickly. Traditional recommender systems mainly focus …