用SOM网络从移动通信数据中识别相似个体

摘要

从移动电话通信数据中挖掘用户有用信息,被认为是富有研究价值的一项工作.利用从94个Nokia 6600用户中收集的实际通信记录,根据用户的通信统计情况,结合用户的调查数据,形成能被SOM网络接受的训练数据集.在此基础上,给出了基于SOM (Self-Organizing Map)的相似个体识别系统SSRS(Similary Subject Recognition System),该系统在训练好的SOM网络支持下,能够对群体中的个体进行有效分类,从而为预测个体将来行为奠定基础.%Data collected from mobile phones have the potential to provide insight into the community's individual classification. Using the reality data collected from 94 Nokia 6600 users,a training dataset fed to SOM neural network was generated, the training dataset consists of user's correspondence statistics and survey data. A Similary Subject Recognition System(SSRS) building on SOM neural network was designed and realized. The system SSRS can carry on the effective classification to community's individual and lay the foundation of forecasting the individual future behavior.