Nowadays, the volume of online information is growing and it is difficult to find the required
information. Effective strategies such as recommender systems are required to overcome …

Recommender systems are a key technology for many applications, such as e-commerce,
streaming media, and social media. Traditional recommender systems rely on collaborative …

Recommender systems (RS) are information filtering systems that attempt to predict a user's
rating or preference for an item. It addresses the issue of information overload by providing …

Pairwise preference information, which involves users expressing their preferences by
comparing items, plays a crucial role in decision-making and has recently found application …

Group recommendation systems are crucial in applications such as group travel or collective
entertainment. Conventional approaches have achieved notable success by matching the …

Recommender Systems are useful information filtering tools that have reduced information
overload over the web. Collaborative filtering (CF) is one of the extensively used …

Recommendation systems have proved to be a compelling performance in overcoming the
data overload problem in many domains, such as e-commerce, e-health, and transportation …

Stroke and many other neural disorders affecting motor functions lead to a significant
degradation in the quality of life. The solution to the problem can be found in integrating …

Human sentiment prevalent in online dialogues largely governs the formation of
communities in online social networks. These recommendation methods helps in filtering …

The increasing number of electronic transactions on the Internet has given rise to the design
of recommendation systems. The main objective of these systems is to give …