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Extracting Significant Mobile Phone Interaction Patterns Based on Community Structures

机译:基于社区结构提取重要的手机交互模式

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Mobile phones have emerged as an essential part of people's lives. The data produced from them can be utilized to derive the spatio-temporal information of their users' whereabouts. We can obtain a rich data set of human activities, interactions, social relationships, and mobility. Hence, it has been possible to explore these information sources with applications ranging from disaster management to disease epidemiology. In this paper, we have focused on the use of call detail records to explore and interpret patterns embedded in interaction flows of people through their mobile phone calls. To do so, we consider the geographical context of subscribers/celltowers to discover structures of spatio-temporal interactions and communities' patterns in Macau. We have explored the inter and intra-polygon interaction flows. The results suggest that subscribers tend to communicate within a spatial-proximity community. In order to delineate relatively contiguous objects with similar attribute values, we have implemented an efficient hierarchical clustering approach. By identifying key objects and their close associates and exploring their communication patterns, we can detect shared interests and dominant interactions that influence societal patterns. Such insight is useful for resource optimization in network planning, content distribution, and urban planning.
机译:手机已成为人们生活中必不可少的一部分。从他们那里产生的数据可以用来推导出他们用户下落的时空信息。我们可以获得有关人类活动,互动,社会关系和流动性的丰富数据集。因此,有可能探索这些信息源,其应用范围从灾难管理到疾病流行病学。在本文中,我们集中于使用呼叫详细记录来探索和解释嵌入在人们通过他们的移动电话的交互流中的模式。为此,我们考虑订户/蜂窝塔的地理环境,以发现澳门的时空互动结构和社区格局。我们已经研究了多边形间和多边形内的交互流。结果表明,订户倾向于在空间邻近社区内进行通信。为了描绘具有相似属性值的相对连续的对象,我们实现了一种有效的层次聚类方法。通过识别关键对象及其密切联系者,并探索他们的沟通方式,我们可以检测到影响社会模式的共同利益和主导互动。这种见解对于网络规划,内容分配和城市规划中的资源优化很有用。

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