{"title":"通信社区组织结构分析的一种算法","authors":"Ying Hou, Hao-xiang Shen, Lixiong Liu, Hai Huang","doi":"10.1109/ICICISYS.2010.5658415","DOIUrl":null,"url":null,"abstract":"The purpose of communication community structure detection in a network is to cluster weighted complex network. By learning from traditional clustering algorithm, OPTICS, an algorithm is designed to detect communication community and analyze its structure. This algorithm considers the effect and detects communication community based on its communication intensity. The detection result is organized in multi distinguishing granular to provide hierarchical structural organization in the communication community. Experiments showed that this algorithm is effective in detecting communication community and analyzing organizational structure.","PeriodicalId":339711,"journal":{"name":"2010 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithm for communication community organizational structure analysis\",\"authors\":\"Ying Hou, Hao-xiang Shen, Lixiong Liu, Hai Huang\",\"doi\":\"10.1109/ICICISYS.2010.5658415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of communication community structure detection in a network is to cluster weighted complex network. By learning from traditional clustering algorithm, OPTICS, an algorithm is designed to detect communication community and analyze its structure. This algorithm considers the effect and detects communication community based on its communication intensity. The detection result is organized in multi distinguishing granular to provide hierarchical structural organization in the communication community. Experiments showed that this algorithm is effective in detecting communication community and analyzing organizational structure.\",\"PeriodicalId\":339711,\"journal\":{\"name\":\"2010 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Intelligent Computing and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICISYS.2010.5658415\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Intelligent Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICISYS.2010.5658415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An algorithm for communication community organizational structure analysis
The purpose of communication community structure detection in a network is to cluster weighted complex network. By learning from traditional clustering algorithm, OPTICS, an algorithm is designed to detect communication community and analyze its structure. This algorithm considers the effect and detects communication community based on its communication intensity. The detection result is organized in multi distinguishing granular to provide hierarchical structural organization in the communication community. Experiments showed that this algorithm is effective in detecting communication community and analyzing organizational structure.