Yanchang Zhao

Yanchang Zhao is a Postdoctoral Research Fellow in Data Sciences & Knowledge Discovery Research Lab, Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering & IT, University of Technology, Sydney, Australia. His research interests focus on association rules, sequential patterns, clustering and post-mining. He has published more than 30 papers on the above topics, including six journal articles and two book chapters. He served as a chair of two international workshops, and a program committee member for 11 international conferences and a reviewer for 8 international journals and over a dozen of international conferences.

Publications

Rare Class Association Rule Mining with Multiple Imbalanced Attributes
Rare Class Association Rule Mining with Multiple Imbalanced Attributes
Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang, Hans Bohlscheid. © 2010. 10 pages.
In this chapter, the authors propose a novel framework for rare class association rule mining. In each class association rule, the right-hand is a target class while the...
Recent Advances of Exception Mining in Stock Market
Recent Advances of Exception Mining in Stock Market
Chao Luo, Yanchang Zhao, Dan Luo, Yuming Ou, Li Liu. © 2010. 21 pages.
This chapter aims to provide a comprehensive survey of the current advanced technologies of exception mining in stock market. The stock market surveillance is to identify market...
Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction
Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction
Yanchang Zhao, Chengqi Zhang, Longbing Cao. © 2009. 394 pages.
There is often a large number of association rules discovered in data mining practice, making it difficult for users to identify those that are of particular interest to them....
Association Rules: An Overview
Association Rules: An Overview
Paul D. McNicholas, Yanchang Zhao. © 2009. 10 pages.
Association rules present one of the most versatile techniques for the analysis of binary data, with applications in areas as diverse as retail, bioinformatics, and sociology. In...
Data Clustering
Data Clustering
Yanchang Zhao, Longbing Cao, Huaifeng Zhang, Chengqi Zhang. © 2009. 11 pages.
Clustering is one of the most important techniques in data mining. This chapter presents a survey of popular approaches for data clustering, including well-known clustering...