COMP 537: Knowledge Discovery and Data Mining in Databases

Spring 2006

Room 2463, Tuesday/Thursday 1:30pm -- 2:50pm

Instructor  Qiang Yang (qyang at cs.ust.hk; Office: Room 3563, 2358-8768)
Office Hours: TuThur 10:30 to 11:30am

Teaching Assistant: Jeff Pan J.F. (TA's Tutorial and Assignment Web Site)

Data Mining Class Newsgroup: hkust.cs.class.537

Course Description

Data mining has emerged as a major frontier field of study in recent years.  Aimed at extracting useful and interesting patterns and knowledge from large data repositories such as databases and the Web, the field of data mining integrates techniques from database, statistics  and artificial intelligence. This course will provide a broad overview of the field, preparing  the students with the ability to conduct research in the field. 

Online Course Material:

·         Lecture Slides

·         Assignments

·         Topics and Papers for Class Presentations

·         Final Project Requirements

·         Useful Links and Data Sets (including KDD CUP information)

Marking Scheme: 

Depending on the number of students, the workload and marking scheme are as follows:

The classes will be divided into two halves roughly: in the first half, I will deliver lectures and students do their assignments.  In the second half, we will read some interesting papers together.  The instructor and students will give critiques on the papers.  For the final project, I will help you find an interesting topic which hopefully will lead to a publication in your area of interest.

Books:

  1. Data Mining -- Practical Machine Learning Tools and Techniques with Java  Implementations by Ian Witten and Eibe Frank, Morgan Kaufmann Publishers.
  2. Data Mining -- Concepts and Techniques by Jiawei Han and Micheline  Kamber. Morgan Kaufmann Publishers.

Background Requirement: PG Students of Computer Science Department