Հարությունյան Մ., Մխիթարյան Կ., Арутюнян М., Мхитарян К.
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.
oai:arar.sci.am:258909
ՀՀ ԳԱԱ Հիմնարար գիտական գրադարան
Aug 18, 2025
Jul 24, 2020
17
https://arar.sci.am/publication/282041
Edition name | Date |
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Information-Theoretic Approach to Community Detection Problem | Aug 18, 2025 |
Haroutunian. Mariam E. Narek S. Pahlevanyan
Haroutunian. Mariam E. Lilit A. Ter-Vardanyan
Haroutunian. Mariam E. Varazdat K. Avetisyan
Haroutunian. Mariam E. Arthur R. Muradyan
Haroutunian. Mariam E. Tonoyan, Smbat A.
E. P. Serrano M. I. Troparevsky M. A. Fabio Գլխավոր խմբ․՝ Մ․ Մ․ Ջրբաշյան (1966-1994) Ռ․ Վ․ Համբարձումյան (1994-2009) Ա․ Ա․ Սահակյան (2010-)