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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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Abstract [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.
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Received: 31 October 2014
Published: 11 June 2015
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