Parallelized Jaccard-Based Learning Method and MapReduce Implementation for Mobile Devices Recognition from Massive Network Data

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...

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Bibliographic Details
Published in:	China communications Vol. 10; no. 7; pp. 71 - 84
Main Authors:	Liu Jun, Li Yinzhou, Cuadrado, F., Uhlig, S., Lei Zhenming
Format:	Journal Article
Language:	English
Published:	China Communications Magazine Co. Ltd 01.07.2013 Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications,Beijing 100876, China%Department of Electronic Engineering and Computer Science, Queen Mary, University of London, London E1 4NS, UK
Subjects:	Computational modeling data mining Data models distributed computing Distributed processing Jaccard coefficient measurement MapReduce Mobile communication Mobile computing mobile device recognition Mobile handsets Object recognition 基础学习方法客户端模式并行化模型识别移动网络运营商移动设备网络数据 mobile device recognition Jaccard coefficient measurement data mining distributed computing MapReduce
ISSN:	1673-5447
Online Access:	Get full text
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