Objectives and Topics

Solving complex practical problems often requires the integration of data and knowledge from different relevant sources and further takes uncertainty and impreciseness into account. This gives rise to the demand for innovative methodologies and efficient techniques of managing and integrating various types of data and knowledge with uncertainty/imprecision so as to ultimately improve the solution to any such complex problems in practice. This symposium aims to provide a forum for exchanges of research results, ideas for and experience of application among researchers and practitioners involved with all aspects of uncertainty management and application.

Its objectives are outlined as follows:

to bring together researchers working on uncertainty formalisms in information and knowledge systems;
to attract researchers working in social sciences (economics, business, management and environmental sciences) who are interested in applying uncertainty-related tools and techniques;
to bring together researchers and practitioners in order to foster the collaboration on research and application involving uncertainty management; and
to present and discuss open research problems and novel applications.
The topics of the Symposium includes (but are not limited to):

Theory and Methodology:

Uncertainty formalisms: Bayesian probability, Dempster-Shafer theory, imprecise probability, random sets, rough sets, fuzzy sets and interval methods; logics for uncertainty reasoning
Information fusion and knowledge integration in uncertain environments
Decision making under various types of uncertainty
Aggregation operators
Copulas for dependence modelling
Granular and soft computing
Type-2 Fuzz set
Applications:

Data mining and knowledge discovery
Ontology engineering and Semantic Web
Software engineering
Medical informatics and bioinformatics
Ranking and recommendation systems
Kansei engineering and evaluation
Engineering management
Supply chain management
Management of services
Environmental and economics sciences
Social Network Analysis
Social Network Mining
Sponsorship

Beihang University, China
University of Bristol, UK
Japan Advanced Institute of Science and Technology, Japan
Springer
Lecture Notes in Artificial Intelligence
Elsevier
International Journal of Approximate Reasoning

Special Issues

International Journal of Approximate Reasoning (Elsevier)