Coupled Behavior Analysis with Applications
Hui Xiong
Associate Professor
Rutgers University
Abstract:
Coupled behaviors refer to the activities of one to many actors who are associated with each other in terms of certain relationships. With increasing network and community-based events and applications, such as group-based crime and social network interactions, behavior couplings contribute to the causes of eventual business problems. Effective approaches for analyzing coupled behaviors are not available, since existing methods mainly focus on individual behavior analysis and overlook coupling relationships. This talk discusses the problem of coupled behavior analysis and its problem-solving. Combined pattern mining and a Coupled Hidden Markov Model (CHMM)-based approach are illustrated to model and detect complex behavior patterns and abnormal group-based behaviors.
Short-Biography:
Longbing Cao is a professor of information technology at the University of Technology Sydney (UTS). He got one PhD in Intelligent Sciences and another in Computing Science. He is the Director of the Advanced Analytics Institute at UTS. He is also the Research Leader of the Data Mining Program at the Australian Capital Markets Cooperative Research Centre. He is a Senior Member of IEEE, SMC Society and Computer Society. His primary research interests include data mining and machine learning, behavior informatics, agent mining, multi-agent systems, and open complex intelligent systems. He initiated and is leading the research on behavior informatics, domain driven data mining, and agent mining. He works/worked with several tier-1 organizations on enterprise data mining, such as Australian Commonwealth Government Agency Centrelink, Westpac Banking Group, AMP, HCF, Credit Swiss, and Shanghai Stock Exchange.