01 Nov, 2018 (Thu)
10:00 am - 11:00 am
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Dr. Won-Yong Shin
Department of Computer Science and Engineering
Dankook University, South Korea.
The discovery of community structures in social networks has gained significant attention since it is a fundamental problem in understanding the networks’ topology and functions. However, most social network data tend to be collected from partially observable networks. In this seminar, I address a new problem of seamlessly detecting community structures in the context of such an incomplete network, which deals with a non-trivial integration of graph recovery and community detection. Our proposed framework consists of 1) estimation of the missing part of the network, 2) selection and addition of influential nodes by ranking, and 3) discovery of community structures. The benefits from resulting more complete community structures are finally investigated.
Biography of the speaker:
Won-Yong Shin is currently a Tenured Associate Professor in the Department of Computer Science and Engineering at Dankook University, South Korea. He received the Ph.D. degree in Electrical Engineering and Computer Science from KAIST, South Korea, in 2008. In 2009, he joined the School of Engineering and Applied Sciences at Harvard University as a Postdoctoral Fellow and was promoted to a Research Associate in 2011. From 2015 to 2017, he served as a Chair of the Department of Mobile Systems Engineering at Dankook. He has also been directing the Software Global Cooperation Center at Dankook since 2017. He is now on sabbatical leave and has been in research stay at many institutions including Heidelberg University, Harvard Medical School, and the University of Hong Kong.
Dr. K.B. Huang
Most seminars are open to the general public, free of charge, unless otherwise stated. Registration is not required. Arrangement for car parking facilities on campus please contact us for details.
For enquiries, please contact:
Department of Electrical and Electronic Engineering,
Room 601, Chow Yei Ching Building,
Pokfulam Road, Hong Kong
Tel: (852) 2859 7093