Batch dynamic algorithm to find k-core hierarchies

Kasimir Gabert, Ali Pinar, Ümit V. Çatalyürek
{"title":"Batch dynamic algorithm to find k-core hierarchies","authors":"Kasimir Gabert, Ali Pinar, Ümit V. Çatalyürek","doi":"10.1145/3534540.3534694","DOIUrl":null,"url":null,"abstract":"Finding k-cores in graphs is a valuable and effective strategy for extracting dense regions of otherwise sparse graphs. We focus on the important problem of maintaining cores on rapidly changing dynamic graphs, where batches of edge changes need to be processed quickly. Many prior dynamic algorithms focus on the problem of maintaining a core decomposition. This finds vertices that are dense in some subgraph, but the subgraph itself is not returned. We develop a new dynamic batch algorithm to maintain cores, with their connected subgraphs, that improves efficiency over processing edge-by-edge. We implement our algorithm and experimentally show that with it core queries can be returned on rapidly changing graphs quickly enough for interactive applications. For 1 million edge batches, on many graphs we run over 100x faster than processing edge-by-edge while remaining under re-computing from scratch.","PeriodicalId":309669,"journal":{"name":"Proceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3534540.3534694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Finding k-cores in graphs is a valuable and effective strategy for extracting dense regions of otherwise sparse graphs. We focus on the important problem of maintaining cores on rapidly changing dynamic graphs, where batches of edge changes need to be processed quickly. Many prior dynamic algorithms focus on the problem of maintaining a core decomposition. This finds vertices that are dense in some subgraph, but the subgraph itself is not returned. We develop a new dynamic batch algorithm to maintain cores, with their connected subgraphs, that improves efficiency over processing edge-by-edge. We implement our algorithm and experimentally show that with it core queries can be returned on rapidly changing graphs quickly enough for interactive applications. For 1 million edge batches, on many graphs we run over 100x faster than processing edge-by-edge while remaining under re-computing from scratch.
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
批处理动态算法查找k核层次结构
在图中寻找k核对于提取稀疏图的密集区域是一种有价值且有效的策略。我们专注于在快速变化的动态图上维护核心的重要问题,其中需要快速处理批量边缘变化。许多先前的动态算法都关注于核心分解的维护问题。这将找到在某些子图中密集的顶点,但不返回子图本身。我们开发了一种新的动态批处理算法来维护内核及其连接的子图,从而提高了逐边处理的效率。我们实现了我们的算法,并通过实验证明,使用它可以在快速变化的图上快速返回核心查询,足以用于交互式应用程序。对于100万个边缘批,在许多图上,我们的运行速度比逐边处理快100倍,同时仍然需要从头开始重新计算。
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
Knowledge graph representation learning and graph neural networks for language understanding Converting property graphs to RDF: a preliminary study of the practical impact of different mappings Multilayer graphs: a unified data model for graph databases Batch dynamic algorithm to find k-core hierarchies Anti-vertex for neighborhood constraints in subgraph queries
×
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