首页> 外文会议>Proceedings of the 14th ACM international conference on modeling, analysis and simulation of wireless and mobile systems. >Multidimensional Modeling and Analysis of Wireless Users Online Activity and Mobility: A Neural-networks Map Approach
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Multidimensional Modeling and Analysis of Wireless Users Online Activity and Mobility: A Neural-networks Map Approach

机译:无线用户在线活动和移动的多维建模和分析:一种神经网络映射方法

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User online behavior and interests will play a central role in future mobile networks. We introduce a systematic method for large-scale multi-dimensional modeling and analysis of online activity and mobility for thousands of mobile users across 79 buildings over a variety of web domains. We propose a modeling approach based on kind of neural-networks, called self-organizing maps (SOM), for discovering, organizing and visualizing different mobile users' trends from billions of WLAN records. We find surprisingly that users' trends based on domains and locations can be accurately modeled using a self-organizing map with clearly distinct characteristics. We also find many non-trivial correlations between different types of web domains and locations.
机译:用户的在线行为和兴趣将在未来的移动网络中发挥核心作用。我们为大规模的多维建模和在线活动和移动性分析提供了一种系统化的方法,可以跨79个建筑物,跨多个网络域对成千上万的移动用户进行在线活动和移动性分析。我们提出一种基于神经网络的建模方法,称为自组织映射(SOM),用于从数十亿条WLAN记录中发现,组织和可视化不同的移动用户趋势。我们惊奇地发现,可以使用具有明显不同特征的自组织映射来准确地建模基于域和位置的用户趋势。我们还发现不同类型的Web域和位置之间存在许多非平凡的关联。

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