Information-Theoretic Approach to Community Detection Problem

Authors

  • Mariam E. Haroutunian Institute for Informatics and Automation Problems of NAS RA
  • Karen K. Mkhitaryan Institute for Informatics and Automation Problems of NAS RA

Keywords:

Community detection, Stochastic block model, Network theory, Clustering, Information theory

Abstract

Real world complex networks possess hidden information called communities or clusters, which are composed of nodes that are tightly connected within communities and weakly connected between communities. Investigation of communities proved to have countless applications in different sciences such as computer science and machine learning, biology, economics, and social networks. Parallel to the development of various detection algorithms, probabilistic network models also gained more attention, particularly stochastic block model which is a generative model for random graphs generating networks with community structure. This paper explores the state of the art on the connections of stochastic block model with information theory

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Published

2021-12-10

How to Cite

Haroutunian, M. E., & Mkhitaryan, K. K. . (2021). Information-Theoretic Approach to Community Detection Problem. Mathematical Problems of Computer Science, 47, 50–61. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/133