Aiming at discovering target customers,this article establishes the value assessment system for government& corporate customers according to the level,stability and accessibility of customer value.With 137 custome...Aiming at discovering target customers,this article establishes the value assessment system for government& corporate customers according to the level,stability and accessibility of customer value.With 137 customers as samples,it builds the government & corporate customer value assessment system through analytic hierarchy process(AHP) and identifies target government &corpora te customers by indicator optimization,model fitting and cluster analysis.All these achievements help accurate identification of high-value government and corporate customers and optimization of resource allocation for customer service.展开更多
The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this pape...The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this paper,we propose a novel method for mobile device model recognition by using statistical information derived from large amounts of mobile network traffic data.Specifically,we create a Jaccardbased coefficient measure method to identify a proper keyword representing each mobile device model from massive unstructured textual HTTP access logs.To handle the large amount of traffic data generated from large mobile networks,this method is designed as a set of parallel algorithms,and is implemented through the MapReduce framework which is a distributed parallel programming model with proven low-cost and high-efficiency features.Evaluations using real data sets show that our method can accurately recognise mobile client models while meeting the scalability and producer-independency requirements of large mobile network operators.Results show that a 91.5% accuracy rate is achieved for recognising mobile client models from 2 billion records,which is dramatically higher than existing solutions.展开更多
Nowadays,mobile operators in China mainland are facing fierce competition from one to another,and their focus of customer competition has,in general,shifted from public to corporate customers.One big challenge in corp...Nowadays,mobile operators in China mainland are facing fierce competition from one to another,and their focus of customer competition has,in general,shifted from public to corporate customers.One big challenge in corporate customer management is how to identify fake corporate members and potential corporate members from corporate customers.In this study,we have proposed an identification method that combines the rule-based and probabilistic methods.Through this method,fake corporate members can be eliminated and external potential members can be mined.The experimental results based on the data obtained from a local mobile operator revealed that the proposed method can effectively and efficiently identify fake and potential corporate members.The proposed method can be used to improve the management of corporate customers.展开更多
基金The work presented in this study is supported by the National Natural Science Foundation of China （Grant No.71372046）. As the authors of this paper, we＇d like to express our sincere gratitude to China enterprise research center, Tsinghua University. Since without the inspiring academic atmosphere, we could hardly come up with the creativity of this study. Besides, we also appreciate the cooperation of our subjects who were all students of our university.
文摘Aiming at discovering target customers,this article establishes the value assessment system for government& corporate customers according to the level,stability and accessibility of customer value.With 137 customers as samples,it builds the government & corporate customer value assessment system through analytic hierarchy process(AHP) and identifies target government &corpora te customers by indicator optimization,model fitting and cluster analysis.All these achievements help accurate identification of high-value government and corporate customers and optimization of resource allocation for customer service.
基金supported in part by the National Natural Science Foundation of China under Grant No.61072061the National Science and Technology Major Projects under Grant No.2012ZX03002008the Fundamental Research Funds for the Central Universities under Grant No.2012RC0121
文摘The ability of accurate and scalable mobile device recognition is critically important for mobile network operators and ISPs to understand their customers' behaviours and enhance their user experience.In this paper,we propose a novel method for mobile device model recognition by using statistical information derived from large amounts of mobile network traffic data.Specifically,we create a Jaccardbased coefficient measure method to identify a proper keyword representing each mobile device model from massive unstructured textual HTTP access logs.To handle the large amount of traffic data generated from large mobile networks,this method is designed as a set of parallel algorithms,and is implemented through the MapReduce framework which is a distributed parallel programming model with proven low-cost and high-efficiency features.Evaluations using real data sets show that our method can accurately recognise mobile client models while meeting the scalability and producer-independency requirements of large mobile network operators.Results show that a 91.5% accuracy rate is achieved for recognising mobile client models from 2 billion records,which is dramatically higher than existing solutions.
基金supported by the Youth Research and Innovation Program in Beijing University of Posts and Telecommunications under Grants No. 2012RC1006,No. 2012RC1008the National Key Basic Research Program of China (973 Program) under Grant No.2012CB315805and the National Natural Science Foundation of China under Grant No.71172135
文摘Nowadays,mobile operators in China mainland are facing fierce competition from one to another,and their focus of customer competition has,in general,shifted from public to corporate customers.One big challenge in corporate customer management is how to identify fake corporate members and potential corporate members from corporate customers.In this study,we have proposed an identification method that combines the rule-based and probabilistic methods.Through this method,fake corporate members can be eliminated and external potential members can be mined.The experimental results based on the data obtained from a local mobile operator revealed that the proposed method can effectively and efficiently identify fake and potential corporate members.The proposed method can be used to improve the management of corporate customers.
