資料探勘研究與實務
Data Mining Research & Practice
| 節 | 週四 |
|---|---|
A 18:30–19:20 | 資料探勘研究與實務 MB311 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
The main objective of this class is to study techniques and applications of data mining, drawing work from areas including database technology, artificial intelligence, and knowledge-based systems. This course will cover Data Warehousing and Data Mining, as well as some topics related to Text Mining and Recommender Systems. Students are required to accomplish project assignments on the implementation and experiment on mining data from various application domains.
Homework (15%), Project & Presentation (25%), Midterm (30%), Final (30%)
- Introduction
- Data Preprocessing
- Data Warehousing
- Attribute-Oriented Induction
- Mining Association Rules
- Classification
- Cluster Analysis
- Text Mining;
- Recommender Systems
| 週次 | 主題 |
|---|---|
| 第 1 週 | Overview |
| 第 2 週 | Data Preprocessing |
| 第 3 週 | Data Warehousing |
| 第 4 週 | Data Warehousing |
| 第 5 週 | Attribute-Oriented Induction |
| 第 6 週 | Mining Association Rules |
| 第 7 週 | Mining Association Rules |
| 第 8 週 | Classification |
| 第 9 週 | Classification |
| 第 10 週 | Classification |
| 第 11 週 | Midterm |
| 第 12 週 | Cluster Analysis |
| 第 13 週 | Cluster Analysis |
| 第 14 週 | Text Mining |
| 第 15 週 | Text Mining |
| 第 16 週 | Recommender Systems |
| 第 17 週 | Recommender Systems |
| 第 18 週 | Final exam |
"Data Mining: Concepts and Techniques", 2nd ed., Morgan Kaufmann Publishers, 2006, by Jiawei Han and Micheline Kamber Introduction to Data Mining, Addison-Wesley, 2006 by Pang-Ning Tan, Michael Steinbach and Vipin Kumar
- 地點
- MB 305
- 時間
- Thur. pm 5:30 ~ 6:30
- 聯絡方式
- dliu@iim.nctu.edu.tw