The use of online social networks has made significant progress in recent years as the use
of the Internet has become widespread worldwide as the technological infrastructure and the …

With the recent growth in the number of IoT devices, the amount of personal, sensitive, and
important data flowing through the global network have grown rapidly. Additionally, the …

The most basic and significant issue in complex network analysis is community detection,
which is a branch of machine learning. Most current community detection approaches, only …

Large-scale group decision making (LSGDM) is characterized by a large number of
participators, multiple groups and a mass of decision data provided by the participators. With …

With the emergence of the Internet-of-Things (IoT), artificial intelligence, and communication
technologies, cyber-physical systems (CPS) have revolutionized the engineering paradigm …

Overlapping graph clustering is essential to understand the nature and behavior of real
complex systems including human interactions, technical systems and transportation …

Besides the topological structure, there are additional information, ie, node attributes, on top
of the plain graphs. Usually, these systems can be well modeled by attributed graphs, where …

In this paper we describe a novel algorithm based on Game Theory for Community
Detection in Online Social Networks. Extending several Game Theoretic approaches that …

The wide application of computer technology promotes the development of large-scale
group decision making. However, with the increase of the number of people involved in …

Community detection is one of the most important tasks in network analysis. It is increasingly
clear that quality measures are not sufficient for assessing communities and structural …