东北大学学报:自然科学版 ›› 2017, Vol. 38 ›› Issue (12): 1691-1696.DOI: 10.12068/j.issn.1005-3026.2017.12.005

• 信息与控制 • 上一篇    下一篇

面向移动通信网络的局部扩张群组构造方法

李婕1, 王兴伟2, 郭静1, 于超1   

  1. (1. 东北大学 计算机科学与工程学院, 辽宁 沈阳110169; 2. 东北大学 软件学院, 辽宁 沈阳110169)
  • 收稿日期:2017-03-27 修回日期:2017-03-27 出版日期:2017-12-15 发布日期:2018-01-02
  • 通讯作者: 李婕
  • 作者简介:李婕(1982-),女,辽宁沈阳人,东北大学副教授; 王兴伟(1968-),男,辽宁盖州人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目( 61572123,61502092); 国家杰出青年基金资助项目(71325002); 中国博士后科学基金资助项目(2016M591449); 教育部-中国移动科研基金资助项目(MCM20160201); 中央高校基本科研业务费专项资金资助项目(N151604001).

Clique Percolation Based Local Fitness Method for User Clustering in Telecommunication Network

LI Jie1, WANG Xing-wei2, GUO Jing1, YU Chao1   

  1. 1. School of Computer Science & Engineering, Northeastern University, Shenyang 110169, China; 2. School of Software, Northeastern University, Shenyang 110169, China.
  • Received:2017-03-27 Revised:2017-03-27 Online:2017-12-15 Published:2018-01-02
  • Contact: WANG Xing-wei
  • About author:-
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摘要: 移动运营商为了拓展新业务,需要增强对用户资源的了解,因此通过大数据分析技术深入分析移动通信系统中的用户行为数据.基于移动通信网络中的用户通话记录提出了一种基于复杂网络聚类算法的用户社交群组构造算法.该算法通过分析用户的通话记录,建立用户间联系紧密度模型.基于局部扩张原理和派系过滤算法进行用户群组构造.鉴于移动通话系统的巨大数据量,采用基于MapReduce编程模型的并行化设计.分别在模拟数据集和中国移动真实数据集下对该算法进行了验证,实验结果表明,该方法具有较好的性能,是可行且有效的.

关键词: 移动通信网络, 联系紧密度, 群组构造, 复杂网络, MapReduce

Abstract: To expand new business, the telecommunication companies need to understand their users deeply. So the data of the user behavior was analyzed in the telecommunication system by using the big data analyzing technology. A clique percolation based local fitness method was proposed for weighted network algorithm (CLFMw) based on the call logs of users in the telecommunication network. The social relationships were established from all of the call connections. Based on the local fitness method (LFM) and the clique percolation method (CPM), the user group was constructed with CLFMw algorithm. According to the massive data sets of the telecommunication system, parallelization design was used based on the MapReduce programming model. Finally, the group construction algorithm is verified by the simulation data set and the real data set for China Mobile. The experimental results show that this method is well performed but also feasible and effective.

Key words: telecommunication networks, relationship closeness, group construction, complex network, MapReduce

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