Group decision-making processes can be supported by group recommender systems that
help groups of users obtain satisfying decision outcomes. These systems integrate a …

In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …

As a step beyond traditional personalized recommendation, group recommendation is the
task of suggesting items that can satisfy a group of users. In group recommendation, the core …

Tripartite graph-based recommender systems markedly diverge from traditional models by
recommending unique combinations such as user groups and item bundles. Despite their …

A news-recommendation system is designed to deal with massive amounts of news and
provide personalized recommendations for users. Accurately modeling of news and users is …

Group recommendation systems are widely applied in social media, e-commerce, and
diverse platforms. These systems face challenges associated with data privacy constraints …

Due to the popularity of group activities in social media, group recommendation becomes
increasingly significant. It aims to pursue a list of preferred items for a target group. Most …

Recommendation to groups of users is a challenging subfield of recommendation systems.
Its key concept is how and where to make the aggregation of each set of user information …

Recommendation systems have shifted from personalization for individual users to
consensus for groups as a result of people's growing tendency to join groups to participate …

Group recommendation has garnered significant attention recently, aiming to suggest items
of interest to groups. Most deep learning-based approaches for group recommendation …