A study on community detection in multilayer networks

IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of High Speed Networks Pub Date : 2023-03-30 DOI:10.3233/jhs-222052

Venkatakrishna Rao Katakamsetty, D. Rajani, P. Srikanth

引用次数: 0

Abstract

Studying complex networks is essential for a better understanding of network science. Many studies have been done on single-layer networks in complex networks. After the advancement and widespread usage of the internet and social media networks, performing community detection in multilayer networks becomes essential to reach more people and work with different personalities on different platforms. Motivated by this observation, this paper has studied types of networks, metrics, measures, and community detection using deep learning-based models in multilayer networks. This survey can play a significant role in analyzing and understanding multilayer networks.

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多层网络中社区检测的研究

研究复杂网络对于更好地理解网络科学至关重要。对复杂网络中的单层网络进行了大量的研究。在互联网和社交媒体网络的进步和广泛使用之后，在多层网络中进行社区检测对于接触更多的人以及在不同平台上与不同个性的人合作变得至关重要。基于这一观察结果，本文在多层网络中使用基于深度学习的模型研究了网络类型、度量、度量和社区检测。这项研究对分析和理解多层网络具有重要意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of High Speed Networks Computer Science-Computer Networks and Communications

CiteScore

1.80

自引率

11.10%

发文量

期刊介绍： The Journal of High Speed Networks is an international archival journal, active since 1992, providing a publication vehicle for covering a large number of topics of interest in the high performance networking and communication area. Its audience includes researchers, managers as well as network designers and operators. The main goal will be to provide timely dissemination of information and scientific knowledge. The journal will publish contributed papers on novel research, survey and position papers on topics of current interest, technical notes, and short communications to report progress on long-term projects. Submissions to the Journal will be refereed consistently with the review process of leading technical journals, based on originality, significance, quality, and clarity. The journal will publish papers on a number of topics ranging from design to practical experiences with operational high performance/speed networks.