A Local Clustering Algorithm for Connection Graphs

Q3 Mathematics Internet Mathematics Pub Date : 2013-12-14 DOI:10.1080/15427951.2014.968295
F. Graham, Mark Kempton
{"title":"A Local Clustering Algorithm for Connection Graphs","authors":"F. Graham, Mark Kempton","doi":"10.1080/15427951.2014.968295","DOIUrl":null,"url":null,"abstract":"We give a clustering algorithm for connection graphs, that is, weighted graphs in which each edge is associated with a d-dimensional rotation. The problem of interest is to identify subsets of small Cheeger ratio that have a high level of consistency, i.e., that have a small edge boundary and for which the rotations along any distinct paths joining two vertices are the same or within some small error factor. We use PageRank vectors as well as tools related to the Cheeger constant to give a clustering algorithm that runs in nearly linear time.","PeriodicalId":38105,"journal":{"name":"Internet Mathematics","volume":"11 1","pages":"333 - 351"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/15427951.2014.968295","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15427951.2014.968295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 11

Abstract

We give a clustering algorithm for connection graphs, that is, weighted graphs in which each edge is associated with a d-dimensional rotation. The problem of interest is to identify subsets of small Cheeger ratio that have a high level of consistency, i.e., that have a small edge boundary and for which the rotations along any distinct paths joining two vertices are the same or within some small error factor. We use PageRank vectors as well as tools related to the Cheeger constant to give a clustering algorithm that runs in nearly linear time.
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
连接图的局部聚类算法
我们给出了连接图的聚类算法,即每条边与一个d维旋转相关联的加权图。感兴趣的问题是识别具有高度一致性的小Cheeger比率子集,即具有较小的边缘边界,并且沿着连接两个顶点的任何不同路径的旋转是相同的或在一些小误差因子内。我们使用PageRank向量以及与Cheeger常数相关的工具来给出一个在接近线性时间内运行的聚类算法。
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
Internet Mathematics
Internet Mathematics Mathematics-Applied Mathematics
自引率
0.00%
发文量
0
期刊最新文献
Graph search via star sampling with and without replacement Preferential Placement for Community Structure Formation A Multi-type Preferential Attachment Tree Editorial Board EOV A Theory of Network Security: Principles of Natural Selection and Combinatorics
×
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