0


加权图和断开的组件:模式和生成器

Weighted Graphs and Disconnected Components: Patterns and a Generator
课程网址: http://videolectures.net/cmulls08_mcglohon_wgdc/  
主讲教师: Mary McGlohon
开课单位: 卡内基梅隆大学
开课时间: 2009-03-29
课程语种: 英语
中文简介:
绝大多数早期的工作都集中在图形上,这些图形都是连接的(通常忽略除了巨大连接组件之外的所有组件),并且未加权。在这里,我们研究了许多真实的加权图,并报告了新节点在社交网络中加入和形成链接的方式的惊人发现。激励性问题如下:图表中的连接组件如何形成并随时间变化?新节点加入网络后会发生什么 - 重复边缘有多常见?我们研究了各种各样的真实图表(引文网络,社交媒体中的网络,互联网流量等);并做出以下贡献:*我们观察到非巨型连通分量似乎在稳定大小,*我们观察到边缘上的权重遵循几个幂律与令人惊讶的指数,并且(c)我们提出了一个直观的,生成的图形模型遵循观察模式的增长。与Leman Akoglu和Christos Faloutsos共同合作。
课程简介: The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and unweighted. Here we study numerous, real, weighted graphs, and report surprising discoveries on the way in which new nodes join and form links in a social network. The motivating questions were the following: How do connected components in a graph form and change over time? What happens after new nodes join a network– how common are repeated edges? We study nu- merous diverse, real graphs (citation networks, networks in social media, internet traffic, and others); and make the following contributions: * we observe that the non-giant connected components seem to stabilize in size, * we observe the weights on the edges follow several power laws with surprising exponents, and (c) we propose an intuitive, generative model for graph growth that obeys observed patterns. Joint work with Leman Akoglu and Christos Faloutsos.
关 键 词: 加权图; 网络; 新节点
课程来源: 视频讲座网
最后编审: 2020-06-22:chenxin
阅读次数: 59