{"title":"A multi-label community discovery algorithm based on the community kernel","authors":"Xiao Han, Yun Liu, Zhen-Jiang Zhang, Jian Li, Fei Xiong","doi":"10.1145/2925995.2926011","DOIUrl":null,"url":null,"abstract":"The main research content is to study and design a feasible multi-label community discovery algorithm for the overlapping community network in this article. This community discovery algorithm has low time complexity, and can conveniently realize the overlapping community discovery. Through the experiment to verify the feasibility and effect of this algorithm, compared this multi-label community discovery algorithm with part of the existing community discovery algorithm from two aspects in time and the classification results in the data sets, confirm the feasibility of this community discovery algorithm.","PeriodicalId":159180,"journal":{"name":"Proceedings of the The 11th International Knowledge Management in Organizations Conference on The changing face of Knowledge Management Impacting Society","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the The 11th International Knowledge Management in Organizations Conference on The changing face of Knowledge Management Impacting Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2925995.2926011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The main research content is to study and design a feasible multi-label community discovery algorithm for the overlapping community network in this article. This community discovery algorithm has low time complexity, and can conveniently realize the overlapping community discovery. Through the experiment to verify the feasibility and effect of this algorithm, compared this multi-label community discovery algorithm with part of the existing community discovery algorithm from two aspects in time and the classification results in the data sets, confirm the feasibility of this community discovery algorithm.