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现实世界网络的动力学

Dynamics of Real-world Networks
课程网址: http://videolectures.net/um05_guerrero_iixum/  
主讲教师: Jure Leskovec
开课单位: 斯坦福大学
开课时间: 2007-11-22
课程语种: 英语
中文简介:
在我们最近的工作中,我们发现了时间演化网络的有趣且不直观的模式,这些模式改变了过去做出的一些基本假设。观察演化模式的主要目的是开发模型,这些模型解释控制网络演化的过程。然后可以将此类模型拟合到实际网络中,并用于生成逼真的图形或对其特性进行形式化解释。此外,我们的工作有广泛的应用:我们可以发现异常的图和异常值,设计更好的图采样算法,预测未来的图结构,并进行网络演化的仿真。这项研究的另一个重要方面是对网络中“局部”模式和传播结构的研究。我们旨在确定网络的构建模块,并找到这些模块对信息或病毒在网络上传播的影响方式。我们最近的工作包括研究在大型人对人产品推荐网络中的影响力扩散及其对购买的影响。我们还对博客圈上信息的传播进行建模,并提出算法来有效地找到网络中的有影响力的节点。进一步的工作将包括三个研究领域。我们将继续研究图生成和演化的模型。其次,我们将分析大型在线通信网络,并设计模型,以研究用户特征和地理位置如何与通信和网络模式相关。第三,我们将把影响力在推荐网络中的传播扩展到Web上的Blog,通过查找有影响力的Blog并分析其影响模式来研究信息如何在Web上传播。
课程简介: In our recent work we found interesting and unintuitive patterns for time evolving networks, which change some of the basic assumptions that were made in the past. The main objective of observing the evolution patterns is to develop models that explain processes which govern the network evolution. Such models can then be fitted to real networks, and used to generate realistic graphs or give formal explanations about their properties. In addition, our work has a wide range of applications: we can spot anomalous graphs and outliers, design better graph sampling algorithms, forecast future graph structure and run simulations of network evolution. Another important aspect of this research is the study of "local" patterns and structures of propagation in networks. We aim to identify building blocks of the networks and find the patterns of influence that these block have on information or virus propagation over the network. Our recent work included the study of the spread of influence in a large person-to-person product recommendation network and its effect on purchases. We also model the propagation of information on the blogosphere, and propose algorithms to efficiently find influential nodes in the network. Further work will include three areas of research. We will continue investigating models for graph generation and evolution. Second, we will analyze large online communication networks and devise models on how user characteristics and geography relate to communication and network patterns. Third, we will extend the work on the propagation of influence in recommendation networks to blogs on the Web, studying how information spreads over the Web by finding influential blogs and analyzing their patterns of influence. ; :  Thesis Committee: : Christos Faloutsos (Chair) : Avrim Blum : John Kleinberg (Cornell University) : John Lafferty
关 键 词: 采样算法; 图生成模型; 图演化模型; 通信网络; 设计模型
课程来源: 视频讲座网
最后编审: 2021-12-21:liyy
阅读次数: 24