主题:Data Analytics: a framework of Granular Computing
主讲人:Witold Pedrycz
地点:松江校区二号学院楼226室
时间:2016-03-21 10:00:02
组织单位: 信息学院 数字化纺织服装技术教育部工程研究中心
Biography：
Witold Pedrycz 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. He holds an appointment of special professorship in the School of Computer Science, University of Nottingham, UK. In 2009 Dr. Pedrycz waselected a foreign member of the Polish Academy of Sciences. In 2012 he was elected 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 fuzzysets and neurocomputing. In 2007 he received a prestigious Norbert Wiener awardfrom the IEEE Systems, Man, and Cybernetics Council. He is a recipient of the IEEE Canada Computer Engineering Medal 2008. In 2009 he has received a Cajastur Prize for Soft Computing from the European Centre for Soft Computing for “pioneering and multifaceted contributions to Granular Computing”. In 2013 he was awarded a Killam Prize. In the same year he received a Fuzzy Pioneer Award 2013 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 intensively involved ineditorial activities. He is an Editor-in-Chief of Information Sciences, Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley), and Journal of Granular Computing(Springer). He currently serves as an Associate Editor of IEEE Transactions on Fuzzy Systems and is a member of a numberof editorial boards of other international journals.
Abstract：
The apparent challenges in data analytics inherently associate with large volumes of data,data variability, and a quest for transparency and interpretability of obtained results. We advocate that information granules play a pivotal role in addressing these key challenges. We demonstrate that a framework of Granular Computing along with a diversity of its formal settings offers a badly needed conceptual and algorithmic setting instrumental for data analytics.
We elaborate on selected ways in which information granules and their processing address help in coping with abundance of data. A suitable perspective built with the aid of information granules is advantageous in realizing a suitable level of abstraction and forming sound, problem-oriented tradeoffs among precision of results, easiness of their interpretation, value of the results and their stability. All those aspects emphasize importance of actionability and interestingness of the produced findings.
Discussed are ways of forming information granules carried out on a basis of abundant data. We show an involvement of efficient granular mechanisms facilitating an inclusion of domain knowledge and making the results of ensuing data analytics user-centric.The development of information granules of higher type and higher order is advocated and their unique role in realizing a hierarchy of processing and coping with adistributed nature of available data is presented.
The facet of variability of data is addressed effectively by invoking the mechanisms of transfer learning applied to the adjustment of information granules.