M. Canu, Marie-Jeanne Lesot, Adrien Revault d'Allonnes
{"title":"Overlapping Community Detection by Local Decentralised Vertex-Centred Process","authors":"M. Canu, Marie-Jeanne Lesot, Adrien Revault d'Allonnes","doi":"10.1109/ICDMW.2016.0019","DOIUrl":null,"url":null,"abstract":"This paper focuses on the identification of overlapping communities, allowing nodes to simultaneously belong to several communities, in a decentralised way. To that aim it proposes LOCNeSs, an algorithm specially designed to run in a decentralised environment and to limit propagation, two essential characteristics to be applied in mobile networks. It is based on the exploitation of the preferential attachment mechanism in networks. Experimental results show that LOCNeSs is stable and achieves good overlapping vertex identification.","PeriodicalId":373866,"journal":{"name":"2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)","volume":"1022 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2016.0019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper focuses on the identification of overlapping communities, allowing nodes to simultaneously belong to several communities, in a decentralised way. To that aim it proposes LOCNeSs, an algorithm specially designed to run in a decentralised environment and to limit propagation, two essential characteristics to be applied in mobile networks. It is based on the exploitation of the preferential attachment mechanism in networks. Experimental results show that LOCNeSs is stable and achieves good overlapping vertex identification.