Abstract Information extracted from social network services promise to improve the accuracy
of recommender systems in various domains. Against this background, community detection …

Recommender Systems learn users' preferences and tastes in different domains to suggest
potentially interesting items to users. Group Recommender Systems generate …

In today's society, recommendations are becoming increasingly important. With the advent of
the Social Web and the growing popularity of Social Networks, where users explicitly …

Recommender system is an emerging field of research with the advent of World Wide Web
and E-commerce. Recently, an increasing usage of social networking websites plausibly …

Purpose The purpose of this paper is to propose an approach to generate recommendations
for groups on the basis of social factors extracted from a social network. Group …

Recommender systems are important tools that provide information items to users, by
adapting to their characteristics and preferences. Usually items are recommended to …

This paper presents a general formalism for Recommender Systems based on Social
Network Analysis. After introducing the classical categories of recommender systems, we …

The goal of this tutorial is to expose participants to the current research on social
recommender systems (ie, recommender systems for the social web). Participants will …

Joint analysis of data from multiple information repositories facilitates uncovering the
underlying structure in heterogeneous datasets. Single and coupled matrix-tensor …

As the exponential growth of information generated on the World Wide Web, Social
Recommendation has emerged as one of the hot research topics recently. Social …