Title: "Fuzzy Approaches to Information Fusion"

Abstract: Fusion is a major issue in all steps of the management of information, from data representation to data mining and decision-making, from basic granules of information to consensus of opinions or semantic interpretation of situations. The complexity of data is due to various factors : heterogeneous media, large size available data on the web or provided by all kinds of sensors, incomplete data bases, imprecise or subjective information granules, the reliability of sources, to mention a few of them. Fuzzy approaches provide interesting solutions to cope with such problems. We will address two main levels in information fusion. The first one is technical and concerns basic needs in image processing, prototype construction or classifier fusion. The second one is more abstract and deals with the interpretation of results, the recognition of high level features in images or videos, or the issue of information scoring.

Bernadette Bouchon-Meunier is a director of research at the National Center for Scientific Research, head of the department of Databases and Machine Learning in the Computer Science Laboratory of the University Paris 6. Graduate from the Ecole Normale Superieure at Cachan, she received the degrees of B.S. in Mathematics and Computer Science, Ph.D. in Applied Mathematics and D. Sc. in Computer Science from the University of Paris. Editor-in-Chief of the International Journal of Uncertainty, Fuzziness and Knowledge-based Systems (World Scientific), she is also a member of the editorial board of the International Journal of Approximate Reasoning, Fuzzy Sets and Systems, International Journal of Fuzzy Systems, International Journal of Information Technology and Intelligent Computing, Journal of Uncertain Systems. She is the (co)-editor of 21 books and the (co)-author of four books in French and one in vietnamese on Fuzzy Logic and Uncertainty Management in Artificial Intelligence. She is a co-founder and co-executive director of the International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU) held every other year since 1986. She is an IEEE senior member and an International Fuzzy Systems Association fellow. Her present research interests include approximate and similarity-based reasoning, as well as the application of fuzzy logic and machine learning techniques to decision-making, data mining, risk forecasting, information retrieval and user modelling.