Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …

The description of an item plays a pivotal role in providing concise and informative
summaries to captivate potential viewers and is essential for recommendation systems …

Currently, the Internet contains a large amount of information, which must then be filtered to
determine suitability for certain users. Recommender systems are a very suitable tool for this …

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

Recommender systems enable users to access products or articles that they would
otherwise not be aware of due to the wealth of information to be found on the Internet. The …

With the rapid development of Information Technology, there exist massive amounts of data
available on the Internet, which result in a severe information overload problem. Especially …

Movie recommendation in mobile environment is critically important for mobile users. It
carries out comprehensive aggregation of user's preferences, reviews, and emotions to help …

There is growing research interest in recommendation as a multi-stakeholder problem, one
where the interests of multiple parties should be taken into account. This category subsumes …

Recommender systems employ recommendation algorithms to predict users' preferences to
items. These preferences are often represented as numerical ratings. However, existing …

Collaborative Filtering (CF) is one of the most extensively used technologies for
Recommender Systems (RS), it shows an improved intelligent searching mechanism for …