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New Technology of Library and Information Service  2015, Vol. 31 Issue (5): 80-87    DOI: 10.11925/infotech.1003-3513.2015.05.11
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Analysis of Mobile User Behaviors with Telecommunication Data
Huang Wenbin, Xu Shanchuan, Ma Long, Wang Jun
Department of Information Management, Peking University, Beijing 100871, China
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[Objective] This paper proposes a user model to understand mobile user behaviors. [Methods] Mobile user behaviors based on communication records from a Chinese telecom, including 10 thousand mobile users in a week with 40 thousand calls and 2 million network requests with locational information are analyzed. 14 fundamental indicators from the data are adopted based on four different categories, namely consumption level, call volume, network request, and amount of movement. [Results] Four user types, regular motion with large conversation, erratically motion with high network accessing, stay-in with economization, and erratically motion with high consumption, are finally deduced in this study by using K-means clustering method. [Limitations] Because of the limitation of user number and the quantity of data, complex machine learning methods are not used to create user model. [Conclusions] The results are valuable references to improve personalized services in mobile applications.

Key wordsUser behavior analysis      Mobile user study      Cluster      Data mining     
Received: 31 October 2014      Published: 11 June 2015
:  G35  

Cite this article:

Huang Wenbin, Xu Shanchuan, Ma Long, Wang Jun. Analysis of Mobile User Behaviors with Telecommunication Data. New Technology of Library and Information Service, 2015, 31(5): 80-87.

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