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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性的多维建模与分析:一种神经网络地图方法

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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:用户在线行为和利益将在未来的移动网络中发挥核心作用。我们介绍了一种系统方法,用于大规模多维建模和分析在各种网络域中的79个建筑物上的数千个移动用户的数千个移动用户。我们提出了一种基于神经网络的类型的建模方法,称为自组织地图(SOM),用于发现,组织和可视化数十亿个WLAN记录的不同移动用户的趋势。我们令人惊讶地发现,使用自组织地图可以使用自组织地图进行准确地建模用户的基于域和位置的用户的趋势。我们还发现不同类型的Web域和位置之间的许多非普通相关性。

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