学术讲座：InvestigatingDynamic Networks
应国际学院的邀请，英国伦敦玛丽女王大学（Queen Mary, University of London）理查德·克莱格（Richard Clegg）博士将为广大师生作题为《Investigating dynamic networks》的学术报告。
讲座题目:Investigating dynamic networks
主讲人: Dr.Richard Clegg ——英国伦敦玛丽女王大学
时间: 2017年11月24日（周五）上午10:00 -- 12:00
地点:西土城校区教三楼3-437
讲座内容:动态网络主要研究互连的网络节点随时间变化的特点和规律。凡是互相连接的对象集合均可视为网络：城市道路（通过街道连接的交通网络）、社会网络（例如Wechat，通过在线交互形成的个人网络）、因特网（通过电子链路构建的计算机网络）。
本讲座首先介绍各种网络之间的结构相似性（如朋友圈与大规模因特网在数学描述／含义上，具有类似的结构），然后讨论偏好连接（preferential attachment）法则，及基于该假设的网络增长／变化模型。偏好连接法则只是真实世界网络的一种近似，因此Richard Clegg博士将重点阐述其研究成果FETA（Frameworkfor Evolving Topology Analysis,演进拓扑分析框架）在动态网络描述和分析方面的性能。
该讲座为前沿讲座，欢迎全校师生踊跃参加。
国际学院
2017年11月19日
附：
Short Bio of Dr. Richard Clegg:
RichardG. Clegg is a Lecturer in Networks at Queen Mary University of London. His PhD in mathematics and statistics from the University of York was gained in2005. His research interests include investigations of the dynamic behaviour ofnetworks and measurement of network traffic statistics.
Brief introduction of this talk:
In thisshort talk I will introduce the study of dynamic networks, how networks ofconnected items evolve as time goes on. The networks can be any collection ofconnected objects. A city's roads can be seen as a network of junctionsconnected by streets; A group of people can be seen as individuals connected byfriendships; A social network like Wechat can be seen as individuals connectedby their online interactions; The Internet can be seen as a group of computernetworks connected by electronic links.
Iwill show how many very different types of networks can be shown to have asimilar structure. A network of friends has a similar structure mathematicallyto the large scale Internet. A law known as preferential attachment has beenhypothesised to cover how such networks might grow. However, this law is onlyapproximate for the study of real world networks. I will show how my work onFETA (Framework for Evolving Topology Analysis) provides a way to introduce aflexible group of models of networks and also how it provides a reliable methodto show which model is best to explain a given network.
