南京师范大学学报（工程技术版）Issue(4)：77-83,7.
基于Group Lasso的多源电信数据离网用户分析
Group Lasso-Based Feature Selection for Off-network Analysis in Multisource Teledata
摘要
Abstract
With the intensified competition in the industry, customer churn analysis is becoming one of the most significant tasks for the telecom companies,which might lead great financial loss to them. Thus,using the data to predict potential off-network customers and then making business decisions to retain these customers,have drawn lots of attention nowadays. In this paper, we present a Group Lasso-based feature selection method to predict the latent off-network customers by analyzing the corresponding multisource teledata. Specifically, we utilize the cross-validation strategy to choose the optimal sets of feature groups. Extensive experiment results show that the proposed approach has the superior performance(the Precision value is 10% higher than the other methods)on a real telecom dataset derived by a certain city in a prefectural city of Jiangsu.关键词
电信企业/客户流失/多源数据/特征选择/Group LassoKey words
telecom companies/customer churn/multisource data/feature selection/Group Lasso分类
信息技术与安全科学引用本文复制引用
孙良君,范剑锋,杨琬琪,史颖欢,高阳,周新民..基于Group Lasso的多源电信数据离网用户分析[J].南京师范大学学报（工程技术版）,2014,(4):77-83,7.基金项目
国家自然科学基金(61035003、61175042、61021062、61305068)、江苏省科技厅项目( BK2011005、BK20130581)、新世纪人才项目(NCET-10-0476)、江苏省医疗专项(BL2013033)、江苏省高校研究生科研创新计划项目(CXZZ13_0055) （61035003、61175042、61021062、61305068）
