Title: Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management
Behavior is ubiquitous and behavior intelligence and insight play an important role in data and business problem solving. Behavior Informatics emerges as an important tool for discovering behavior intelligence and insight. Behavior Informatics takes a top-down approach to systematically and deeply represent, model, reason about, and aggregate behaviors, consisting of behavior subjects and objects, and their operations and operation properties and relationships; as well as a bottom-up approach to analyze and learn behavior occurrences, non-occurrences, dynamics, impact, and utility. These are based on the construction of behavior model, behavior actor model, and behavior relation representation, and the formation of behavioral data and the characterization of behavioral properties, evolution, and impact, etc.. This talk introduces some of applications of behavior informatics in core business, capital markets and government services for handling complex individual and group behaviors, interactions between clients and service providers, personalized and early prevention and intervention of abnormal behaviors, and active and tailored management of clients. The real-life case studies show the applications of behavior informatics for handling high-impact behaviors, high-utility behaviors, coupled group behaviors, and even non-occurring behaviors in risk management in banking, capital markets, and government services, and highly significant economic benefits and social impact by applying the resultant behavior insight and behavior intelligence.
Longbing Cao is a professor at the University of Technology Sydney. He holds a PhD in Computing Science and another PhD in Pattern Recognition and Intelligent Systems.
He has been working on data science and analytics research, development, education, and enterprise applications since he was a CTO and then joined academia. Focusing on addressing real-world challenging and common problems, he has been developing theories, tools and applications for areas including behaviour informatics, non-IID learning, actionable knowledge discovery, and complex intelligent systems, in addition to issues generally concerned in data mining and machine learning. He has published some 300 publications, and three monographs. In real-life analytics, his team has successfully delivered many large analytical projects for government and business organizations in Australia and overseas, resulting in significant amounts of dollar savings and mentions in government, industry, media and OECD reports. In education and professional services, he significantly contributed to the establishment of the Data Science and Knowledge Discovery lab at UTS in 2007, the Advanced Analytics Institute and the degrees Master of Analytics (Research) and PhD in Analytics at UTS in 2011, the IEEE Task Force on Data Science and Advanced Analytics (DSAA) and IEEE Task Force on Behavior, Economic and Soci-cultural Computing in 2013, the IEEE Conference on Data Science and Advanced Analytics (DSAA) and the ACM SIGKDD Australia and New Zealand Chapter in 2014, and the International Journal of Data Science and Analytics with Springer in 2015. He served as general and program co-chairs on conferences including KDD2015 in Sydney.