Group recommendation has recently drawn a lot of attention to the recommender system
community. Currently, several deep learning-based approaches are leveraged to learn …

Item recommendation is a personalized ranking task. To this end, many recommender
systems optimize models with pairwise ranking objectives, such as the Bayesian …

When deciding where to visit next while traveling in a group, people have to make a trade-off
in an interactive group recommender system between (a) disclosing their personal …

With the prevalence of social media, there has recently been a proliferation of
recommenders that shift their focus from individual modeling to group recommendation …

Psychological factors such as personality, emotions, social connections, and decision
biases can significantly affect the outcome of a decision process. These factors are also …

Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …

Group recommendation research has recently received much attention in a recommender
system community. Currently, several deep-learning-based methods are used in group …

As social animals, attending group activities is an indispensable part in people's daily social
life, and it is an important task for recommender systems to suggest satisfying activities to a …

The recommender system has recently drawn a lot of attention to the communities of
information services and mobile applications. Many deep learning-based recommendation …

Current recommender systems consider the various aspects of items for making accurate
recommendations. Different users place different importance to these aspects which can be …