报 告 人：Witold Pedrycz，加拿大阿尔伯塔大学（University of Alberta, Canada）教授
报告题目：From Data to Information Granules and Symbols
内容简介：Data are omnipresent and come with enormous abundance. We advocate that to efficiently cope with data and exploit their sound usage in system modeling, decision making, control, and classification, they need to be dealt with at a certain level of abstraction. Information granules offer a conceptual and algorithmic setting where the data can be abstracted in a sound and efficient manner. The level of abstraction itself is implied by the nature of the problem under discussion.
Clustering (either objective function-based methods or hierarchical algorithms) deliver a prerequisite for the formation of information granules. We show that they offer some sound mechanism to support the design of information granules with the aid of the principle of justifiable granularity. The principle provides a way to build an information granule such that it is legitimate from the perspective of coverage (experimental legitimacy of the granule) and its semantics (meaning). Along with the generic construct, discussed are various augmentations of the principle. We carefully look at the generative and discriminative aspects of information granules supporting their further usage in the formation of granular artifacts. The considerations are carried out following a general knowledge representation scheme:
data ànumeric prototypesàinformation granules à symbols
Furthermore, a symbolic characterization of information granules is put forward and analyzed from the perspective of semantically sound descriptors of data and relationships among data.
报告人简介：Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. Dr. Pedrycz is a foreign member of the Polish Academy of Sciences and a Fellow of the Royal Society of Canada. Witold Pedrycz has been a member of numerous program committees of IEEE conferences in the area of fuzzy sets and neurocomputing. He is a recipient of the prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society, IEEE Canada Computer Engineering Medal, Cajastur Prize for Soft Computing from the European Centre for Soft Computing, Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.
His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He has published numerous papers in this area. He is also an author of 16 research monographs covering various aspects of Computational Intelligence, data mining, and Software Engineering.
Dr. Pedrycz is vigorously involved in editorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Int. J. of Granular Computing (Springer). He serves on an Advisory Board of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of other international journals.