Main Article Content
Abstract
Identifying communities in social networks is one of the most important tasks nowadays. Social networks are especially relevant for networks represented by large-scale graphics. At the same time, it is important to use approximate methods that lead to near-optimal rather than optimal results within a given time. In this article, we propose to extract the communities based on the method of maximum likelihood similarity by representing them by letters. The community structure search algorithm is described and the performance of the algorithm is illustrated using examples of different views of the octagonal network.. Calculations were carried out using the Maple program.
Keywords
maximum likelihood
Graphics
Communication between teams
Teams section
Maple
Article Details
How to Cite
Dilshodbek, Z., & Bektosh, S. (2023). THE MAXIMUM REALIZATION METHOD OF COMMUNITY GROUPING IN SOCIAL NETWORKS. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4(5), 56-61. https://doi.org/10.17605/OSF.IO/5RQ2S
References
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