朝陽科技大學 091學年度第2學期教學大綱
Data Mining 資料探勘

當期課號 7092 Course Number 7092
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 課堂講授、課堂研討報告、課外作業及專題。 Teaching Materials Sliders and Handouts is used to introduct the basic concepts and methods.
Students are required to present a journal paper during this course.
Severl homeworks are assigned
Final project about the data mining topic is required.
成績評量方式 作業+報告(60%)、期中考試(25%)與期末專題及報告(15%)。 Grading Assignments + Class presentation (60%), Midterm (25%), Project and project documentation (15%).
教師網頁  
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.
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