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China Computer Federation (CCF) Advanced Disciplines Lectures (ADL)

Matrix Factorization Framework for Social Computing

Irwin King

Department of Computer Science and Engineering
The Chinese University of Hong Kong

Abstract

With the emergence of Web 2.0, social networks have becoming an integral and important part of our changing social cultural. With the novel transformative ways to connect, collaborate, and create communities on the Web, the phenomenon of cyber social behaviors have emerged that intrigue researchers and practitioners alike. Currently, we have voluminous data collected from web sites, blogs, wikis, clickthrough data, query logs, tags, etc.~from areas such as social networks, social search, social media, social bookmarks, social news, social knowledge sharing, and social games. These data provide a wealth of information available for us to process, analyze, and mine. The tutorial will introduce the matrix factorization framework for social computing. Topics include, but not limited to singular value decomposition, probabilistic matrix factorization, non-negative matrix factorization, etc. will be presented. Moreover, the tutorial will also provide some applications to demonstrate how these techniques can be used in social computing applications.

Research Interests

Prof. Irwin King's research interests include machine learning, social computing, web intelligence, data mining, big data, and multimedia information processing. In these research areas, he has over 210 technical publications in journals and conferences. In addition, he has contributed over 30 book chapters and edited volumes. Moreover, Prof. King has over 30 research and applied grants. One notable patented system he has developed is the VeriGuide System, which detects similar sentences and performs readability analysis of text-based documents in both English and in Chinese to promote academic integrity and honesty.

Prof. King is the Book Series Editor for “Social Media and Social Computing” with Taylor and Francis (CRC Press). He is also an Associate Editor of the ACM Transactions on Knowledge Discovery from Data (ACM TKDD) and a former Associate Editor of the IEEE Transactions on Neural Networks (TNN). He is a member of a number of Editorial Boards. He is also a member of the Board of Governors of INNS and a Vice-President and Governing Board Member of APNNA. He also serves INNS as the Vice-President for Membership in the Board of Governors.

Dr. King is Professor at the Department of Computer Science and Engineering, The Chinese University of Hong Kong. He received his B.Sc. degree in Engineering and Applied Science from California Institute of Technology, Pasadena and his M.Sc. and Ph.D. degree in Computer Science from the University of Southern California, Los Angeles.

金国庆,香港中文大学计算机科学与工程系教授,加州大学伯克利分校访问教授,社会计算、机器学习、网络智能、信息检索、多媒体处理以及神经网络等领域的资深专家。在上述研究领域中,金教授已公开发表、主播或编纂200余篇期刊、会议论文、书刊及学术著述。他在加州理工学院(帕萨迪纳)获得工程与应用科学学士学位,在南加州大学获得计算机科学的硕士和博士学位。

Presentation Materials

 
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