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以行为模式为特征的交互图的基于事件的框架

An Event-based Framework for Characterizing the Evolutionary Behavior of Interaction Graphs
课程网址: http://videolectures.net/kdd07_asur_aebf/  
主讲教师: Sitaram Asur
开课单位: 俄亥俄州立大学
开课时间: 2007-08-14
课程语种: 英语
中文简介:
交互图在诸如生物信息学,社会学和物理科学等许多领域中无处不在。文献中有许多研究旨在研究和挖掘这些图表。然而,几乎所有人都从静态的角度研究了这些图。随着时间的推移研究这些图的演变可以提供对实体,社区的行为以及它们之间的信息流的巨大洞察。在这项工作中,我们提出了一个基于事件的临界行为模式表征,用于时间变化的交互图。我们使用交互图的非重叠快照,并开发一个框架,用于捕获和识别来自它们的有趣事件。我们使用这些事件来描述个人和社区随时间变化的复杂行为模式。我们演示了行为模式的应用,用于建模进化,链接预测和影响最大化。最后,我们基于我们的框架提出了一个用于不断发展的网络的扩散模型。
课程简介: Interaction graphs are ubiquitous in many fields such as bioinformatics, sociology and physical sciences. There have been many studies in the literature targeted at studying and mining these graphs. However, almost all of them have studied these graphs from a static point of view. The study of the evolution of these graphs over time can provide tremendous insight on the behavior of entities, communities and the flow of information among them. In this work, we present an event-based characterization of critical behavioral patterns for temporally varying interaction graphs. We use non-overlapping snapshots of interaction graphs and develop a framework for capturing and identifying interesting events from them. We use these events to characterize complex behavioral patterns of individuals and communities over time. We demonstrate the application of behavioral patterns for the purposes of modeling evolution, link prediction and influence maximization. Finally, we present a diffusion model for evolving networks, based on our framework.
关 键 词: 交互图; 临界行为; 行为模式
课程来源: 视频讲座网
最后编审: 2019-05-08:lxf
阅读次数: 24