| 當期課號 |
7771 |
Course Number |
7771 |
| 授課教師 |
李金鳳 |
Instructor |
LEE,CHIN FENG |
| 中文課名 |
資料探勘 |
Course Name |
Data Mining |
| 開課單位 |
資訊管理系碩士在職專班一A |
Department |
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| 修習別 |
選修 |
Required/Elective |
Elective |
| 學分數 |
3 |
Credits |
3 |
| 課程目標 |
本課程在導引學生了解何謂資料倉儲(Data Warehouse)系統、資料探勘以及它的應用，資料探勘應用包括預測(Prediction)、分類(Classification)、群聚(Clustering)以及關聯規則(Association rules) 之採掘等範圍。 |
Objectives |
An introduction to data mining and data warehousing: motivation and applications.
Basic data warehousing technology: data cube methods, data warehouse construction and maintenance.
Basic data mining techniques: characterization, association, classification, clustering, and similarity-based mining.
Advanced data mining applications: mining relational and transaction data, mining time-related data, spatial data mining, textual data mining, multimedia data mining, visual data mining, and Web mining. |
| 教材 |
Data Mining: Concepts and Techniques, Jiawei Han and Micheline Kamber , Morgan Kaufmann Pub., 2000.
Data Mining: Introductory and Advanced Topics, Dunham, Prentice Hall, 2002.
Selected Journal or Conference Papers
REFERENCES:
Some recent conference/journal paper collection, (class distribution). |
Teaching Materials |
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| 成績評量方式 |
作業+報告+平時表現(出席率+上課Q&A)+其他、期中與期末考試、期末計畫書+專題報告+期末專題文件)。 |
Grading |
Presentation+numbers of question+Assignments + Class presentation Midterm &Final termsProject and project documentation。 |
| 教師網頁 |
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| 教學內容 |
TOPICS:
An introduction to data mining and data warehousing: motivation and applications.
Basic data warehousing technology: data cube methods, data warehouse construction and maintenance.
Basic data mining techniques: characterization, association, classification, clustering, and similarity-based mining.
Advanced data mining applications: mining relational and transaction data, mining time-related data, spatial data mining, textual data mining, multimedia data mining, visual data mining, and Web mining. |
Syllabus |
OBJECTIVE/DESCRIPTION:
Data Mining and Knowledge Discovery has become an active area of research, attracting people from several disciplines, including database systems, statistics, information retrieval, pattern recognition, AI/machine learning, and data visualization.
The course will introduce data mining and data warehousing, and study their principles, algorithms, implementations, and applications. |