通过独立的顶点中心过程快速发现社区结构局部

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI:10.1145/2808797.2808866

M. Canu, Marcin Detyniecki, Marie-Jeanne Lesot, Adrien Revault d'Allonnes

{"title":"通过独立的顶点中心过程快速发现社区结构局部","authors":"M. Canu, Marcin Detyniecki, Marie-Jeanne Lesot, Adrien Revault d'Allonnes","doi":"10.1145/2808797.2808866","DOIUrl":null,"url":null,"abstract":"This paper addresses the task of community detection and proposes a local approach based on a distributed list building, where each vertex broadcasts basic information that only depends on its degree and that of its neighbours. A decentralised external process then unveils the community structure. The relevance of the proposed method is experimentally shown on both artificial and real data.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fast community structure local uncovering by independent vertex-centred process\",\"authors\":\"M. Canu, Marcin Detyniecki, Marie-Jeanne Lesot, Adrien Revault d'Allonnes\",\"doi\":\"10.1145/2808797.2808866\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the task of community detection and proposes a local approach based on a distributed list building, where each vertex broadcasts basic information that only depends on its degree and that of its neighbours. A decentralised external process then unveils the community structure. The relevance of the proposed method is experimentally shown on both artificial and real data.\",\"PeriodicalId\":371988,\"journal\":{\"name\":\"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)\",\"volume\":\"96 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2808797.2808866\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2808797.2808866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

本文解决了社区检测的任务，并提出了一种基于分布式列表构建的局部方法，其中每个顶点广播的基本信息仅取决于其程度及其邻居的程度。然后，分散的外部流程揭示了社区结构。在人工数据和实际数据上均证明了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Fast community structure local uncovering by independent vertex-centred process

This paper addresses the task of community detection and proposes a local approach based on a distributed list building, where each vertex broadcasts basic information that only depends on its degree and that of its neighbours. A decentralised external process then unveils the community structure. The relevance of the proposed method is experimentally shown on both artificial and real data.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

自引率

0.00%

发文量