Community Detection using Fast Cosine Shared Link Method

Laxmi Chaudhary, Buddha Singh
{"title":"Community Detection using Fast Cosine Shared Link Method","authors":"Laxmi Chaudhary, Buddha Singh","doi":"10.1109/IADCC.2018.8692102","DOIUrl":null,"url":null,"abstract":"Finding communities in a complex network is tedious task. In this paper, we have proposed a Fast Cosine Shared Link (FCSL) method for unveiling and analyzing concealed behavior of the communities in the network. We have used Cosine similarity measure to find the node’s similarity. Further, we have evaluated the time taken to identify the communities in the network. Substantial experiments and results shows the potential of the proposed method to successfully find real world communities in real world network datasets. The experiments we carried out exhibit that our method outperforms other techniques and slightly improve results of the other existing methods, proving reliable results. The performance of methods evaluated in terms of communities, modularity value and time taken to detect the communities in network.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 8th International Advance Computing Conference (IACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IADCC.2018.8692102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Finding communities in a complex network is tedious task. In this paper, we have proposed a Fast Cosine Shared Link (FCSL) method for unveiling and analyzing concealed behavior of the communities in the network. We have used Cosine similarity measure to find the node’s similarity. Further, we have evaluated the time taken to identify the communities in the network. Substantial experiments and results shows the potential of the proposed method to successfully find real world communities in real world network datasets. The experiments we carried out exhibit that our method outperforms other techniques and slightly improve results of the other existing methods, proving reliable results. The performance of methods evaluated in terms of communities, modularity value and time taken to detect the communities in network.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
社区检测使用快速余弦共享链路方法
在一个复杂的网络中寻找社区是一项乏味的任务。在本文中,我们提出了一种快速余弦共享链路(FCSL)方法来揭示和分析网络中社区的隐藏行为。我们使用余弦相似度度量来寻找节点的相似度。此外,我们还评估了识别网络中社区所花费的时间。大量的实验和结果表明,所提出的方法有潜力在现实世界的网络数据集中成功地找到现实世界的社区。实验结果表明,我们的方法优于其他技术,并且比其他现有方法的结果略有改善,证明了结果的可靠性。从社团、模块化值和检测网络社团所需时间三个方面评价了方法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Discovering Motifs in DNA Sequences: A Suffix Tree Based Approach Prediction Model for Automated Leaf Disease Detection & Analysis Blind navigation using ambient crowd analysis HUPM: Efficient High Utility Pattern Mining Algorithm for E-Business Algorithm to Quantify the Low and High Resolution HLA Matching in Renal Transplantation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1