MobileMiner:移动通信中数据挖掘的真实案例研究

Tengjiao Wang, Bishan Yang, Jun Gao, Dongqing Yang, Shiwei Tang, Haoyu Wu, Kedong Liu, J. Pei
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引用次数: 15

摘要

移动通信数据分析经常被用作激发许多数据挖掘问题的后台应用程序。然而,很少有数据挖掘研究人员有机会看到在真实的移动通信数据上工作的数据挖掘系统。在这个演示中,我们在一个真实的移动通信数据集上展示了我们的新系统MobileMiner,它展示了一个使用最先进的数据挖掘技术的商业解决方案的案例研究。MobileMiner自适应地从用户的通话和移动记录流中分析用户的行为。可以根据用户档案进行客户细分和社会社区分析。我们展示了数据挖掘技术如何帮助移动通信数据分析。此外,我们还展示了一些有趣的观察结果,这些观察结果仍然不能被当前的技术所挖掘,因此可能会激发新的研究和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MobileMiner: a real world case study of data mining in mobile communication
Mobile communication data analysis has been often used as a background application to motivate many data mining problems. However, very few data mining researchers have a chance to see a working data mining system on real mobile communication data. In this demo, we showcase our new system MobileMiner on a real mobile communication data set, which presents a case study of business solutions using state-of-the-art data mining techniques. MobileMiner adaptively profiles users' behavior from their calling and moving record streams. Customer segmentation and social community analysis can be conducted based on user profiles. We show how data mining techniques can help in mobile communication data analysis. Moreover, we also show some interesting observations which still cannot be mined by the current techniques, and thus may motivate new research and development.
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