Analysis of the Modern Algorithms’ Accuracy for Communities Identification on Networks when Working with Graph Databases
( Pp. 49-59)

More about authors
Ekaterina D. Kazakova the Faculty of Information Technology and Big Data Analysis
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Abstract:
In this paper, we consider methods for extracting communities in networksusing various algorithms. The Girvan-Newman, Louvain, Walktrap and Leiden algorithms were presented and the results of their application on the Wikipedia graph were analyzed. Various metrics were used to assess the quality of the isolated communities, and the results were stored in the Neo4j graph database. The results showed that the Leiden and Louvain algorithms with a resolution equal to one showed the best results compared to other algorithms.
How to Cite:
Kazakova E.D. Analysis of the Modern Algorithms’ Accuracy for Communities Identification on Networks when Working with Graph Databases. Computational Nanotechnology. 2023. Vol. 10. No. 1. Pp. 49–59. (In Rus.) DOI: 10.33693/2313-223X-2023-10-1-49-59
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Keywords:
network analysis, community detection algorithms, graph databases.


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