社区检测算法综述及其性能比较分析

IF 12.7 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Dipika Singh , Rakhi Garg
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引用次数: 0

摘要

社区检测是一个重要的研究领域。它在社会、生物网络中有各种各样的应用。多年来,已经提出了许多社区检测算法。对社区检测的不同方法也进行了许多调查。但随着多年来提出的算法越来越多,需要对这一领域进行更新和全面的审查。本文试图对2002年至2024年社区检测领域的重要研究成果进行积累。我们还讨论了由不同作者修改和重新实现的重要算法及其优缺点。此外,还阐述了评估社区检测算法和使用的数据集的不同指标。本文将有助于该领域的研究人员获得不同社区检测算法的最新集合以及它们所使用的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey of Community Detection algorithms and its comparative performance analysis
Community Detection is an important area of research. It finds a variety of applications in Social, Biological networks. Many Community Detection algorithms have been proposed over the years. And many surveys have also been conducted on different approaches of Community Detection. But as more and more algorithms have been proposed over the years, a more updated and complete review is required in this area. In this paper we have tried to accumulate important research in the area of Community Detection from the year 2002 to 2024. We have also discussed important algorithms that have been modified and re-implemented by different authors along with its merits and demerits. Moreover, different metrics for the evaluation of Community Detection algorithms and datasets used are also elaborated. This paper will be beneficial for researchers working in this area to get a latest collection of different Community Detection algorithms along with the approaches used in them.
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来源期刊
Computer Science Review
Computer Science Review Computer Science-General Computer Science
CiteScore
32.70
自引率
0.00%
发文量
26
审稿时长
51 days
期刊介绍: Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.
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