Longbing Cao

Longbing Cao is an Associate Professor in Faculty of Engineering & IT, University of Technology, Sydney (Australia). He is the Director of Data Sciences & Knowledge Discovery Research Lab. His research interest focuses on domain driven data mining, multi-agents, and the integration of agent and data mining. He is a chief investigator of two ARC (Australian Research Council) Discovery projects and one ARC Linkage project. He has over 50 publications, including one monograph, two edited books and 10 journal articles. He is a program co-chair of 11 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...
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....
Actionable Knowledge Discovery
Actionable Knowledge Discovery
Longbing Cao. © 2009. 6 pages.
Actionable knowledge discovery is selected as one of the greatest challenges (Ankerst, 2002; Fayyad, Shapiro, & Uthurusamy, 2003) of next-generation knowledge discovery 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...
Domain Driven Data Mining
Domain Driven Data Mining
Longbing Cao, Chengqi Zhang. © 2008. 28 pages.
Quantitative intelligence based traditional data mining is facing grand challenges from real-world enterprise and cross-organization applications. For instance, the usual...
Domain-Driven Data Mining: A Practical Methodology
Domain-Driven Data Mining: A Practical Methodology
Longbing Cao, Chengqi Zhang. © 2008. 18 pages.
Extant data mining is based on data-driven methodologies. It either views data mining as an autonomous data-driven, trial-and-error process or only analyzes business issues in an...
Domain-Driven Data Mining: A Practical Methodology
Domain-Driven Data Mining: A Practical Methodology
Longbing Cao, Chengqi Zhang. © 2006. 17 pages.
Extant data mining is based on data-driven methodologies. It either views data mining as an autonomous data-driven, trial-and-error process or only analyzes business issues in an...