CSC7121
Advanced Topics in Database Systems
Data Mining
Course content
Data mining provides useful tools for the analysis, understanding
and extraction of useful information from huge databases.
Applications range from business, finance, medicine and engineering.
This course will introduce the techniques used in data-mining.
Topics will include clustering, classification, estimation,
forecasting, statistical analysis and visualization tools.
Second Term 2006-2007
Prof. Laiwan Chan
Ho Sin Hang Engineering Building 1016,
Department of Computer Science and Engineering
The Chinese University of Hong Kong
Shatin, New Territories
Email : lwchan 
cse.cuhk.edu.hk
Tel : 2609 8434
Fax : 2603 5024
- 6:30 pm - 9:30 pm Monday, CKB 123
- Examination : 2:15 pm, 28 April 2007 Sat, Lady Shaw Building LT3
Course Objectives
-
to provide a comprehensive understanding of current methodologies used in data mining
- to discuss the strengths and weaknesses of popular data mining technique
- to introduce the whole data mining process
- to present some applications of data mining to real-world problems
Learning Outcomes
After successful completion of this course, students should be able
- to identify the objectives of the real world data mining problems,
- to select and apply the right techniques to solve these problems,
- and to systematically evaluate the results obtained.
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Tan, Steinbach and Kumar, Intorduction to Data Mining, Addison Wesley, 2006.
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Berry, M. & Linoff, G., ``Data Mining Techniques for Marketing,
Sales, and Customer Support'', John Wiley & Sons, 1997.
ISBN: 0-471-17980-9.
-
Joseph P. Bigus,
``Data Mining with Neural Networks, solving business problems
from application development to decision support'',
McGraw Hill, 1996
-
Pieter Adriaans and Dolf Zantinge,
``Data mining'', Addison-Wesley, 1996.
-
Duda, Richard O. and Peter E. Hart.
``Pattern classification and scene analysis'',
New York : Wiley, 1973.
cuhk.cse.csc7121
- 60 % Final Examination (with minimum passing score of 30/100)
- 15 % Assignment
- 25 % Course Project
Last updated :
lwchan