Knowledge Discovery

Knowledge discovery is a non trivial process of identifying effective, novel, potentially useful and ultimately understandable patterns from data sets. Knowledge discovery turns information into knowledge, and finds the hidden knowledge nuggets from data mines, which will contribute to knowledge innovation and the development of knowledge economy.

The course objective is to present the leading data mining methods and their application to real-world problems. The topics covered include: introduction to data mining, data warehouses, association rules, decision trees, neural networks, fuzzy sets, support vector machine, overview of commercial tools for data mining, data preparation, and feature selection. Finally, we describe several real-world data mining projects and discuss some “hot” issues in data mining research. 

References

1. 史忠植. 知识发现. 北京：清华大学出版社，2002

2. 史忠植. 知识发现（第二版）. 北京：清华大学出版社，2011

3. Zhongzhi Shi. Advanced Artificial Intelligence (2nd Edition). New Jersey: World Scientific Publishing, 2020