Topic:Multidimensional symbolic data analysis
Keynote speakers:Richard EMILION，University of Orléans;Paula Brito, University of Porto.
Time:2017. 6.30，9:30-12:00
Conference room:New main building, A928
Host:Prof. Huiwen Wang
Abstract:
With the rapid development of information technology and the advent of big data era, data collection and storage of information has become extremely convenient. In companies of financial industry, government agencies, and other electric business enterprises, through the continuous use of information systems, multi-attribute business data has rapidly accumulated and formed large scale high-dimensional data. To deal with such massive data, the classical statistical models will not only bring great computational pressure, but also losing the visualization and interpretability of the analysis results. To solve the above problem, Diday (1988) proposed the symbolic data analysis method. The classification analysis method is used to divide the massive observation data into several categories, and then use the symbolic data to describe each type of the data. The commonly used symbolic data includes interval data, histogram data, distribution data, and so on. Prof. Paula Brito and Prof. Richard Emilion will introduce several multivariate analysis methods of high dimensional histogram data and distribution datafrom theory to application. The application of these methods will improve the efficient analysis of massive data, and become an advanced tool for data analysis in the field of economic management.
Brief CV of the speakers：
Richard Emilion is a professor in at the Department of Mathematics of University of Orléans. His research interests cover a wide range of probability theory, statistics, applied mathematics, in particular bayesian statistics, dirichlet processes, ergodic theorems.
Paula Brito is aprofessor in Statistics and Data Analysis at the Faculty of Economics (Group of Mathematics and Information Systems) of the University of Porto, also a member of the Laboratory in Artificial Intelligence and Decision Support (LIADD– INESC TEC) of the University of Porto. Her scientific interests include multivariate data analysis, in particular clustering methods, analysis of multidimensional complex data, known as symbolic data, and data analysis using Galois Lattices.
