Longbing Cao - Behavior Informatics 1: Behavior modeling and representation

08:00
Thursday
6
Jun
2013
  • Seminar
Organized by: 
Yves Demazeau, équipe MAGMA
Speaker: 
Professor Longbing Cao, Director of Advanced Analytics Institute, UTS
Teams: 

SEMINAR SERIES OF INTRODUCTION TO BEHAVIOR INFORMATICS

- 06/06/13

  • Topic : Behavior representation, modeling and checking
  • Abstract : The concept of behavior, behavior informatics, visual modeling, formal modeling of behaviors, behavior model checking, and case studies

- 13/06/13

  • Topic : High impact and combined behavior analysis
  • Abstract : Concept of behavior impact, positive/negative behavior, impact-oriented behavior pattern mining and outlier detection, high impact behavior mining, combined behavior pattern mining, early prediction and intervention of high impact behavior, and case studies

- 27/06/13

  • Topic : Group and community behavior analysis
  • Abstract : Concepts of coupling, coupled behavior, coupled behavior analysis, abnormal coupled behavior learning, and case studies

- Bio :

Longbing Cao is a professor of information technology at the Faculty of Engineering and IT, UTS ; and the founding Director of the UTS Advanced Analytics Institute. AAI is the largest research group in Australia focusing on advanced analytics, with broad collaborations with many major local and international organizations.

Longbing was awarded PhD in computing sciences and PhD in intelligent sciences. Before joining UTS, Longbing had several years of research experience in Chinese Academy of Sciences, and working experiences in managing and leading industry and commercial projects in telecommunications, banking and publishing, as manager or chief technology officer. Besides general interest in areas such as data mining, machine learning, artificial intelligence, multi-agent systems and software engineering, Longbing has been initiating and now leading research in particular topics including behavior informatics and computing, non-iidness learning (including object relation learning and pattern relation learning), agent mining, and complex intelligent systems, and in particular enterprise applications of data mining and behavior informatics in the real world.

In Australia, Longbing has solid links with broad-based major business, industry, vendor and government organizations, leading and managing many projects such as in social security, taxation, banking, telecommunication, capital market, insurance, public sector and airline business. During these exercises, Longbing fosters a strong research culture of conducting cutting-edge and applied research inspired by challenging but critical business and social problems, and forming a strong interaction and balance between high quality Research, high calibre analyst Education and high impact Development (so-called RED).

Complex behaviors are widely seen in artificial and natural intelligent systems, on the internet, social and online networks, multi-agent systems, and brain systems. The in-depth understanding of complex behaviors has been increasingly recognized as a crucial means for disclosing interior driving forces, causes and impact on businesses in handling many challenging issues. This forms the need and emergence of behavior informatics, i.e. understand behaviors from computing perspective. Traditional behavior modeling mainly relies on qualitative methods from behavioral science and social science perspectives. The so-called behavior analysis often focuses on human demographic and business usage data, in which behavior-oriented elements are hidden in routinely collected transactional data. As a result, it is ineffective or even impossible to deeply scrutinize native behavior intention, lifecycle, dynamics and impact on complex problems and business issues. In fact, we can develop two directions to explicate a global picture of the behavior informatics : qualitative and quantitative behavior analytics. With the formal representation of coupled behaviors, the qualitative analytics addresses the task of behavior reasoning and verification, while the quantitative research targets behavior learning and evaluation. This reveals significant gaps in the literature for ‘computing’ behaviors especially group and community behaviors. In this series of seminars, we present an overview of behavior informatics, and discuss complex behavior representation and relationships, behavioral feature construction, high-impact behavior analysis, group and coupled behavior analysis etc. Several real-world case studies are demonstrated, including analyzing exceptional market microstructure behaviors, mining for high impact social security behavior patterns, detecting abnormal pool manipulation behaviors, analyzing student learning progression, and analyzing online banking behavior interactions. Behavior informatics creates new opportunities, directions and means for qualitative and quantitative, formal and systematic modeling, learning and analysis of complex behaviors in both physical and virtual organizations.