面向移动通信网络的局部扩张群组构造方法

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.

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

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.