Keynote Speeches
| Modern Service Industry in China: Mining
and Exploring Heterogeneous Data for Service
Oriented Computing |
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Professor Zhaohui Wu
Zhejiang University
China |
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| ABSTRACT: Driven by economic globalization
and information, the world has entered into the service economy
era. In such context, Modern Service Industry in not only
becoming a leading and pillar industry for economic development,
but also an important indicator of measuring the degree of
production socialization and market economic development. As a
matter of course, Service Oriented Computing, as the academic
foundation of Modern Service Industry, attracts lots of
attention in the last decade. In this talk, we will give the
concept and overview of the development trend of Modern Service
Industry in the world, especially the development of Modern
Service Industry in China. Further, we will show how to use some
popular approaches (e.g., Bayes theorem, Graph Mining, etc.) to
mine and explore the massive heterogeneous data in Modern
Service Industry, and how to handle some common problems in
Service Oriented Computing.
BIO: Dr. Zhaohui Wu is a Qiushi Professor of
Zhejiang University and the director of the Institute of
Computer System and Engineering. He is the committee chair of
National S&T Innovation Plan on Modern Service Industry (MSCI)
and the Distinguished Young Scholar of China National Science
Foundation (NSFC). He is the director of MOE’s Research Center
of Intelligence Science and Technique and the head of MOE’s R&D
Center of High-Performance Embedded Computing. He is the
Standing Member and a fellow of the China Computer Federation (CCF).
His research interests include Service Computing and intelligent
systems. Dr. Wu has authored 9 books, more than 200 refereed
papers and over 100 invention patents, as well as 2 national S&T
progress prize II. He is the founding editor-in-chief of
Elsevier’s Big Data Research Journal, the associated editor of
Chinese Journal of Information on Traditional Chinese Medicine
and the founder of three international conferences (ICESS,
CPSCom and MSCI). |
| Knowledge Engineering with Big Data |
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Professor
Xindong Wu
University of Vermont USA |
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| ABSTRACT: Big Data processing concerns
large-volume, growing data sets with multiple, heterogeneous,
autonomous sources, and explores complex and evolving
relationships among data objects. This talk starts with a HACE
theorem (http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6547630)
that characterizes the features of the Big Data revolution, and
proposes a Big Data processing model, from the knowledge
engineering perspective. We analyze the challenging issues in
knowledge discovery, knowledge-base construction, and knowledge
services in the Big Data revolution. BIO:
Xindong Wu is a Professor of Computer Science at the University
of Vermont (USA), a Yangtze River Scholar in the School of
Computer Science and Information Engineering at the Hefei
University of Technology (China), and a Fellow of the IEEE and
the AAAS. He is Steering Committee Chair of the IEEE
International Conference on Data Mining (ICDM), Editor-in-Chief
of Knowledge and Information Systems (KAIS, by Springer), and
Editor-in-Chief of the Springer Book Series on Advanced
Information and Knowledge Processing (AI&KP). Professor Wu is
the 2004 ACM SIGKDD Service Award winner and the 2006 IEEE ICDM
Outstanding Service Award winner, and received the 2012 IEEE
Computer Society Technical Achievement Award "for pioneering
contributions to data mining and applications". |
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