Keynote Speeches

Modern Service Industry in China: Mining and Exploring Heterogeneous Data for Service Oriented Computing
wzh Professor Zhaohui Wu

Zhejiang University
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
wzh Professor Xindong Wu

University of Vermont USA
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 ( 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".