0


社会化搜索基于图的方法

Graph-based Methods for Social Search
课程网址: http://videolectures.net/russir2010_troussov_gmss/  
主讲教师: Alexander Troussov
开课单位: IBM公司
开课时间: 2011-03-18
课程语种: 英语
中文简介:
Web 2.0和Cyber​​infrastructure技术的最新发展创造了大量的计算机中介网络,其中节点可能是人以及“非人类代理”。例如文档,数据集,分析工具和概念。而这些网络变得越来越“多维”。搜索漏洞链接。搜索变得个性化,协作性,社交性。网络模型能够聚合异构信息,基于图形的方法提供了清晰的直觉和优雅的数学来挖掘这些模型。本课程将回顾现代基于图形的方法,包括随机物理方法和聚类方法,以分析表现出高聚类的复杂网络的结构(例如在个体之间的友谊网络中)。我们将介绍这些方法的应用以挖掘大量异构信息,并且我们将演示如何使这些方法了解人们参与的网络维度,包括社交,语义和活动管理维度。
课程简介: Recent developments in Web 2.0 and Cyberinfrastructure technologies create massive computer mediated networks, where the nodes might be people as well as “non-human agents” such as documents, datasets, analytic tools, and concepts. And these networks become more and more “multidimensional”. Search exploits that links. Search becomes personal, collaborative, social. Network models are capable to aggregate heterogeneous information, graph-based methods provide clear intuition and elegant mathematic to mine such models. The course will provide review of modern graph-based methods, including methods of stochastic physics and clustering approaches needed to analyse the structure of complex networks exhibiting high clustering (such as in networks of friendships between individuals). We will present applications of these methods to mining of large volumes of heterogeneous information, and we will demonstrate how to make these methods aware of dimensions of networks where people are involved, including social, semantics, and activity management dimensions.
关 键 词: 网络模型; 现代图形审查方法; 构信息挖掘
课程来源: 视频讲座网
最后编审: 2020-06-28:yumf
阅读次数: 40