Department of MIS. , College of Commerce, NCCU
Professor Tseng, Shu-Feng
(Part One)
NATIONAL CHENGCHI UNIVERSITY
COLLEGE OF COMMERCE
DEPARTMENT OF
MANAGEMENT INFORMATION SYSTEMS
Regular Phd PROGRAM
Seminar in Information Systems and Technology
(資訊技術研究) 2009/Spring
A. Instructor:
Office:
E-mail:
Phone/Fax:
Class Hours:
Office Hours:
Tseng, Shu-Feng (曾淑峰)
Research: Room 261119, 11th Fl., College of Commerce Bldg.
sftseng@nccu.edu.tw
Office: 8661-3129, Mobile: 0921-879265
Tuesday 18:30 – 21:30
Tuesday: 17:00 - 18:00 And by appointment
B. Books
Tan,P.-N., Steinbach, M. and Kumar, V. Introduction to Data Mining,
Addison-Wesley, Pearson International Edition, 2006.
C. Course Objectives
This course provides an interactive discussion for the advanced Information
Technologies and their applications in business environment. In this semester, this 2/3
part of the course focuses on the data mining concepts, techniques, and applications.
The interactive discussion is based on group reading the textbook “Introduction to
Data Mining.” As the final report, students need to run a data mining application
using SAS EDM and compare their relative pros and cons using various data mining
concepts and techniques learned in the textbook readings.
本課程針對所選先進資訊技術主題及其在企業環境應用，進行互動式研討，本學
期這 2/3 部份課程著重於資料發掘概念、技術及應用之探討，互動式研討以共同
研讀一本教科書「資料發掘簡介」進行之。期末報告中，學生須使用 SAS EDM
針對特定資料發掘問題探討課堂學習概念與技巧之應用情境。
D. Grading Policy
Final Report ----------------------------------------- 50 %
Class Presentations --------------------------------- 50 %
Total
100%
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Department of MIS. , College of Commerce, NCCU
Professor Tseng, Shu-Feng
E. Important Notes and Policies
CLASS SCHEDULE
No. Date
Chapter, Subjects and Assignments
Memo
1
2/24
Course Introduction
SAS EDM Installation & Introduction
Tseng
2
3/3
CH1, 31 slides, 15 pages, Introduction
Prediction Problem Description
Tseng
3
3/17
CH2, 68 slides, 69 pages, Data
Search Engine Optimization
A
4
3/24
CH3, 41 slides, 44 pages, Exploring Data
Social Network
B
5
3/31
CH4, 101 slides, 53 pages, Classification:
Basic Concepts, Decision Trees, and Model
Evaluation
B
6
4/7
Regression Analysis
CH10, 25 slides, 29 pages, Anomaly Detection
A
7
4/14
CH6, 82 slides, 77 pages, Association
C
Comments
Analysis: Basic Concepts and Algorithms
8
4/21
CH8, 104 slides, 72 pages
Cluster Analysis: Basic Concepts and
Algorithms
C
9
4/28
Neuron Network(Mid-Term Week)
A
10
5/5
Project Discussion
Tseng
11
5/12
Project Discussion
Tseng
Team A: Paul, Sean, August
Team B: Mika, Donald, J. S.
Team C: Alex, Chicel, Nash
Skip Chapters：
CH5, 88 slides, 108 pages, CH7, 67 slides, 58 pages；CH9, 37 slides, 78 pages
Chapters:
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Department of MIS. , College of Commerce, NCCU
Professor Tseng, Shu-Feng
1 Introduction
2 Data
3 Exploring Data
4 Classification: Basic Concepts, Decision Trees, and Model Evaluation
5 Classification: Alternative Techniques
6 Association Analysis: Basic Concepts and Algorithms
7 Association Analysis: Advanced Concepts
8 Cluster Analysis: Basic Concepts and Algorithms
9 Cluster Analysis: Additional Issues and Algorithms
10. Anomaly Detection
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