报告题目: 在线社交网络中的综合影响传播模型
报告人:Quan Bai 博士
时 间:2018年12月04日上午10:30
地 点:计算机学院112会议室
主 持人:孔燕
报告人简介:
Quan Bai 博士现任教于新西兰奥克兰科技大学工程,计算机与数学科学学院,他分别于2002年和2007年在澳大利亚卧龙岗大学取得硕士和博士学位。博士毕业后,他曾在卧龙岗大学从事博士后研究工作数年,而后就职于澳大利亚科技和产业研究部。Quan Bai 博士的主要研究领域是multi-agent coordination, trust analysis, mining and agent-abased modelling for complex systems. 他从事研究工作数年以来,一共发表学术论文百余篇,其中包含IEEE Trans 系列期刊论文,相关领域其他顶级期刊和顶级学术会议论文共计数十篇,鉴于他的突出贡献,agent领域顶级会议之一 AAMAS 组委会任命他为AAMAS 2020 的会议主席。
报告摘要:
Abstract:
With the widespread of the Internet, the on-line social network with big data is rapidly developing over time. Many enterprises attempt to develop their business by utilizing the power of on-line social networking platforms. A considerable amount of work has focused on how to select a set of influential users to maximize a kind of positive influence in static social networks. However, networks evolve, and the topological structure changes over time. Meanwhile, multiple influences may exist in the on-line social network at the same time. How to mine and adapt the influencers in a dynamic and complex environment becomes a challenging issue. In this talk, I am going to introduce some recent research findings of my group in comprehensive influence propagation modelling, and the utilisation of agent-based techniques in this problem
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计算机与软件学院
2018年12月3日