[Abstract] Networks arising from the real life are concerned with relations between the real objects and became the significant part of the modern life. The important examples include links between web pages, citations of references in scientific papers, social networks of acquaintance or other connections between individuals, electric power grids, etc. The word ”network” is usually used for what mathematicians and a few computer scientists call graphs. A network (graph) is a set of items called vertices with connections between them, called edges. The study of a graph theory is one of the fundamental pillars of discrete mathematics. A social network is a set of people or groups of people with some pattern of contacts or interactions between them. The social networks have been studied extensively since the beginning of 20th century, when the sociologists realized the importance of the understanding how the human society is functioned. The traditional way to analyse a graph is to look at its picture, but this is unusable for the large networks. The new approach to examine properties of graphs has been driven largely by the availability of computers and communication networks, that allow us to analyse data on a scale far larger than before now, see.
Complex networks such as the World Wide Web or the social networks often do not have an engineered architecture but instead of that are self-organized by the actions of a large number of individuals. From these local interactions nontrivial global phenomena can emerge as, for example, small-world properties or a scale-free distribution of the degree. In the small-world networks short paths between almost any two sites exist even though nodes are highly clustered. The Scale-free networks are characterized by a power-law distribution of a nodes degree, defined as the number of its next neighbours, meaning that structure and dynamics of the network are strongly affected by nodes with a great number of connections.
The analysis of social networks is concentrated mainly on uncovering hidden relations and properties of network nodes (vertices). Most of the current approaches are focused mainly on different network types and network coefficients. One of the most relevant features of social networks is the community structure. Since these networks are typically very complex, it is great interest to reduce these networks to much simpler. In this lecture we will present one of the main organizing principles in social network - network communities. Network communities sets of nodes organize into densely linked clusters. Even though detection of such communities is of great interest, understanding the structure communities in large networks remains relatively limited. We present methods of partitioning of graphs that could be interpreted as communities |
[Biography] Václav Snášel's research and development experience
includes over 25 years in the Industry and Academia. He works in a
multi-disciplinary environment involving artificial intelligence,
multidimensional data indexing, conceptual lattice, information
retrieval, semantic web, knowledge management, data compression,
machine intelligence, neural network, web intelligence, data mining
and applied to various real world problems. He has given more than 5
plenary lectures and conference tutorials in these areas. He has
authored/co-authored several refereed journal/conference papers and
book chapters. He has published more than 300 papers. He has
supervised many Ph.D. students from Czech Republic, Jordan, Yemen,
Slovakia, Ukraine and Vietnam.
From 2001 he is a visiting scientist in the Institute of Computer
Science, Academy of Sciences of the Czech Republic. From 2003 he is
vice-dean for Research and Science at Faculty of Electrical
Engineering and Computer Science, VSB-Technical University of Ostrava,
Czech Republic. He is full professor since 2006. Before turning into a
full time academic, he was working with industrial company where he
was involved in different industrial research and development projects
for nearly 8 years. He received Ph.D. degree in Algebra and Geometry
from Masaryk University, Brno, Czech Republic and a Master of Science
degree from Palacky University, Olomouc, Czech Republic.
Besides, the Editor-in-Chief of two journals, he also serves the
editorial board of some reputed International journals. He is actively
involved in the International Conference on Computational Aspects of
Social Networks (CASoN) ; Computer Information Systems and Industrial
Management (CISIM); Evolutionary Techniques in Data Processing (ETID)
series of International conferences. He is a Member of IEEE (USA), ACM
(USA), AMS (USA), SIAM (USA).
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