Providing recommendations to groups of users has become a promising research area,
since many items tend to be consumed by groups of people. Various techniques have been …

In this paper, we present a Multi Agent System aimed to support an user on the realization of
different leisure and tourist activities in a city. The system integrates agents that cooperate to …

Over the last years, some remarkable recommender systems for group of users have been
developed. When using most of these systems, each group member communicates his/her …

Recommender Systems have become fundamental web applications providing
personalized recommendations to users that are suitable to their needs and preferences in …

Recommender System (RS) predicts user's ratings towards items, and then recommends
highly-predicted items to user. In recent years, RS has been playing more and more …

Sparse representation and low-rank matrix decomposition approaches have been
successfully applied to several computer vision problems. They build a generative …

This paper presents an architecture of a contextaware pro-active recommender system. The
system uses contextual information in order to provide recommendations that are more …

In multi-agents recommender systems, agents interact with each other to provide an efficient
recommendation to the end user. Trust is, therefore, important to make these interactions …

This paper presents a multi-agent recommender system in which agents collaborate with
each other to facilitate in providing travel recommendations. A set of rules are organized to …

In multi-agent recommender system, the knowledge degree of an agent and its trust degree
are two main criteria in the decision-making phase. These criteria are used to recommend …