【北航经管学术论坛】
题目：Multidimensional symbolic data analysis
主讲人:Richard EMILION，University of Orléans;
Paula Brito, University of Porto.
时间:2017. 6.30，9:30-12:00
地点:新主楼A928
邀请人:Prof. Huiwen Wang
摘要:
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.
主讲人简介：
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.
经管学院科研办
2017-06-27
