CS591HAN Fall 2005 Advanced Seminar on Data Mining

4:00-5:00pm Wednesday, 3403 Siebel Center

About the Course (Course CRN: 43832)

This is a special topic course on data mining. The course materials will consist of presentation and discussion of research papers and research project reports closely related to the topics in data mining. The students who take CS412—Introduction to Data Mining, or have good background on data mining, database systems, machine learning and/or statistics and who would like to get one unit credit are required to register and attend this course. Other students are welcome to attend. The research papers will be selected from the course supplementary materials (which mainly consists of research papers published recently on data mining and data warehousing).

Prerequisites

Student who are taking or took CS412 (Introduction to Data Mining), CS512 (Data Mining: Principles and Algorithms), CS446 (Machine Learning), or CS411 (Database Systems) or some related statistics courses, and with good background on data mining, statistics, machine learning, and database systems.

Reference Books

The following texts are recommended but not required, for reference, and are also on reserve at Grainger Engineering Library. There are numerous other books or online resources on data mining available.

Data Mining: Concepts and Techniques, 2^nd ed., by Jiawei Han and Micheline Kamber, Morgan Kaufmann, 2006. See the book's home page for errata, course slides, and other reference materials.
T. M. Mitchell, Machine Learning, McGraw Hill, 1997.
T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer-Verlag, 2001
D. J. Hand, H. Mannila, and P. Smyth, Principles of Data Mining, MIT Press, 2001
I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann, 2001

Course Format and Activities

This course will draw materials from the recent data mining literature. Students will study the materials and complete all the course requirements

Assignments

Students are required to hand in half-page abstract for every paper to be presented in class right after the class presentation

Examination

No exam will be given

Course Project

No course project requirement, but those who got good research ideas from the course are encouraged to continue to claim good research results

Evaluation

Students who register for this course will be evaluated based on course presentation and participation.

Jiawei Han