**報告題目**【Soft data analysis】

**時間**：9月18日起每周三下午14:00（共四次）

**地點**：旗山校區數信大樓511

**主講**：Ivo Duntsch 教授

**主辦**：數學與信息學院

**參加對象**：相關專業老師及學生

**報告摘要**：In a sequence of four lectures I shall give an introduction to the theory and applications of soft data analysis.

Lecture 1. I shall present basic principles and concepts of data analysis. These include ex-ploratory and inferential analysis, representativeness of data, data models, measurement theory,interpretation of numbers and scaling artifacts. I shall also introduce and discuss aspects of soft computing.

Lecture 2. The soft approach to data analysis is based on a robust handling of uncertainty and therefore, it is to a large part concerned with approximations. In this lecture I shall give an overview of “qualitative” tools for approximation such as modal operators, rough sets, and formal concept analysis.

Lecture 3. In the third lecture I shall present an application of the soft methods discussed in the previous lectures, namely, assessment of learning via skills and knowledge structures. This is one of a range of cognitive diagnostic models and their relatives.

Lecture 4. Using the concepts of the previous lectures, I shall introduce J.J. Gibson’s “Ecological Approach to Visual Perception” and his concept of affordances. These may be interpreted as relations and have been successfully applied in many fields related to computer science, among them user interfaces, robotics, and autonomous driving.

It will be helpful to have a thorough knowledge of basic mathematical structures, such as sets,relationgs and functions. A good source is the booklet Sets, relations, functions

**報告人簡介**：Ivo Düntsch，Visiting Professor, College of Mathematics and Informatics,Fujian Normal University, Fuzhou, Fujian, PR China