系所

資訊科技與管理研究所

1 年級

課號 / 班別

ms1217 / B

3 學分

科目中文名稱

資料倉儲與探勘(全英語授課)

科目英文名稱

Data Warehouse and Data Mining

每週授課時數

3 小時

必選科目

任課老師

鄒慶士

開課期間

一學期

人數上限

20 人

一、教學目標

Understand fundamental concept and algorithms of data mining and its applications in business and management.

(School core ability: professional knowledge,practical techniques, innovation and research, English language skills; Department core ability: information management profession, hands-on learning, innovation and research)

二、先修科目

Statistics, database and algorithm.

三、教材內容

This course covers basic to advanced topics of data

warehousing and mining. It will present the algorithms and techniques used in data mining. More specifically, it will discuss how to use evolutionary algorithms to transform raw data into useful information in detail.

四、教學方式

Lecture, discussion and presentation

五、參考書籍

Freitas, Alex A. (2002), Data Ming and Knowledge

Discovery with Evolutionary Algorithms,Springer.

(Textbook)Witten, I.H. and Frank, E. (2005),

Data Mining:Practical Machine Learning Tools

and Techniques,2nd Edition,Morgan Kaufmann.

(新月)Dunham, M.H. (2003), Data Mining:

Introductory and AdvancedTopics, Prentice Hall.

(歐亞)Roiger, Richard and Geatz, Michael W.

(2003), Data Mining:A Tutorial-Based Primer,

Addison Wesley. (新月)Berry, Michael J.A.

and Linoff, Gordon (1997),Data Mining

Techniques: For Marketing, Sales, and

CustomerRelationship Management,

John Wiley & Sons. (雙葉)

六、教學進度

Topic 1: Data warehouse and OLAP technology
(Han and Kamber, 2007)
Topic 2: Data cube computation and data generalization
(Han and Kamber, 2007)
Topic 3: Classification
Topic 4: Dependency modeling
Topic 5: Clustering
Topic 6: Inductive bias
Topic 7: Instance-based learning
Topic 8: Data preparation
Topic 9: Genetic algorithms for rule discovery
Topic 10: Genetic programming for rule discovery
Topic 11: Evolutionary algorithms for clustering
Topic 12: Evolutionary algorithms for data preparation
Topic 13: Evolutionary algorithms for discovering fuzzy rules
Topic 14: Scaling up evolutionary algorithms for large data sets
Topic 15: Multi-objective evolutionary algorithms for data mining

七、評量方式

Attendance & discussion 10%, presentation 30%,

mid-term exam.30%, final exam. 30%

八、講義位址