{"title":"Division of mobile social network based on user behavior","authors":"Zhao Pei-kun, Zhao Juan-juan, Wang Wu","doi":"10.1109/ICWAPR.2013.6599307","DOIUrl":null,"url":null,"abstract":"In order to improve the personalized mobile network services, some researchers have employed the social relationship into the acquisition of mobile user's needs. But, when mobile users belong to different communities, their impacts on other mobile users are different. Therefore, in this paper, we propose an improved division of mobile social network based on the mobile user's behaviors. Firstly, we propose a computation of trust including the direct trust and indirect trust based on communications between mobile users. Then, we construct the mobile social network according to the obtained trusts. Afterward, we propose an improved method to divide the mobile social network based on cohesive subgroups. Finally, we perform experiments using the MIT real dataset. Experimental results show that we can get more accurate subgroup division.","PeriodicalId":236156,"journal":{"name":"2013 International Conference on Wavelet Analysis and Pattern Recognition","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2013.6599307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In order to improve the personalized mobile network services, some researchers have employed the social relationship into the acquisition of mobile user's needs. But, when mobile users belong to different communities, their impacts on other mobile users are different. Therefore, in this paper, we propose an improved division of mobile social network based on the mobile user's behaviors. Firstly, we propose a computation of trust including the direct trust and indirect trust based on communications between mobile users. Then, we construct the mobile social network according to the obtained trusts. Afterward, we propose an improved method to divide the mobile social network based on cohesive subgroups. Finally, we perform experiments using the MIT real dataset. Experimental results show that we can get more accurate subgroup division.