當期課號 | 7422 | Course Number | 7422 |
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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 | 資訊管理系碩士班一A | Department | |
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 | |
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 | http://www.cyut.edu.tw/~lcf | ||
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. |