淡江大學資訊管理系 戴敏育 Min-Yuh Day http://mail.im.tku.edu.tw/~myday/ 2011-02-15 資料倉儲 Data Warehousing 992DW01 MI4 二 8,9 15:10-17:00 L413 淡江大學資訊管理系 戴敏育 Min-Yuh Day http://mail.im.tku.edu.tw/~myday/ 2011-02-15
http://mail.im.tku.edu.tw/~myday/
http://mail.im.tku.edu.tw/~myday/
課程資訊 課程名稱:資料倉儲 (Data Warehousing) 授課教師:戴敏育 (Min-Yuh Day) 開課資料:選修 單學期 2學分 上課時間:週二 8,9 (Tue 15:10-17:00) 上課教室:L413
Knowledge Discovery (KDD) Process Data Warehouse: fundamental process for Data Mining and Business Intelligence Data mining: core of knowledge discovery process Pattern Evaluation Data Mining Task-relevant Data Data Warehouse Selection Data Cleaning Data Integration Databases Source: Han & Kamber (2006)
Data Warehouse Data Mining and Business Intelligence Increasing potential to support business decisions End User Decision Making Data Presentation Business Analyst Visualization Techniques Data Mining Data Analyst Information Discovery Data Exploration Statistical Summary, Querying, and Reporting Data Preprocessing/Integration, Data Warehouses DBA Data Sources Paper, Files, Web documents, Scientific experiments, Database Systems Source: Han & Kamber (2006)
課程簡介 本課程介紹資料倉儲的基本概念及技術。 課程內容包括資料倉儲、OLAP、資料探勘、商業智慧、即時分析處理,資料方塊,關聯分析、分類、分群、社會網路分析、文字探勘、與網頁探勘。
Course Introduction This course introduces the fundamental concepts and technology of data warehousing. Topics include data warehousing, data mining, business intelligence, OLAP, data cube, association analysis, classification, cluster analysis, social network analysis, text mining, and web mining.
Objective Students will be able to understand and apply the fundamental concepts and technology of data warehousing.
教學目標之教學策略與評量方法 教學目標 教學策略 評量方法 學生將能夠瞭解及應用資料倉儲的基本概念及技術。 課堂講授、分組討論 出席率、報告、討論、期中考、期末考
授課進度表 週次 月/日 內容(Subject/Topics) 備註 1 100/02/15 Introduction to Data Warehousing 2 100/02/22 Data Warehousing, Data Mining, and Business Intelligence 3 100/03/01 Data Preprocessing: Integration and the ETL process 4 100/03/08 Data Warehouse and OLAP Technology 5 100/03/15 Data Cube Computation and Data Generation 6 100/03/22 Association Analysis 7 100/03/29 Classification and Prediction 8 100/04/05 (放假一天) 100/04/05 (二) 民族掃墓節 9 100/04/12 Cluster Analysis 10 100/04/19 期中考試週
授課進度表(續) 週次 月/日 內容(Subject/Topics) 備註 11 100/04/26 Sequence Data Mining 12 100/05/03 Social Network Analysis and Link Mining 13 100/05/10 Text Mining and Web Mining 14 100/05/17 Project Presentation 15 100/05/24 畢業班考試 16 100/05/31 NA 17 100/06/07 18 100/06/14 期末考試週
教材課本 Data Mining: Concepts and Techniques, Second Edition, Jiawei Han and Micheline Kamber, 2006, Elsevier 參考書籍 資料探勘:概念與方法,王派洲 譯,2008,滄海 資料庫理論與實務SQL Server 2008,施威銘研究室,2010,旗標 Web 資料採掘技術經典,孫惠民,2008,松崗
Data Mining: Concepts and Techniques (Second Edition) http://www.amazon.com/Data-Mining-Concepts-Techniques-Management/dp/1558609016
http://www.cs.uiuc.edu/homes/hanj/bk2/
http://www.cs.uiuc.edu/homes/hanj/bk2/bk3_slidesindex.htm
作業與學期成績計算方式 批改作業篇數 學期成績計算方式 1篇(Team Term Project) 期中考成績:30 % 期末考成績:30 % 作業成績: 20 % (Team Term Project) 其他(課堂參與及報告討論表現): 20 %
Term Project 參與 NTCIR 國際競賽 Open Topic Project NTCIR (NII Test Collection for IR Systems) Project NTCIR -9 (July 2010 -December 2011) December 6-9, 2011, NII, Tokyo, Japan NTCIR-9 RITE Recognizing Inference in TExt @NTCIR9 http://artigas.lti.cs.cmu.edu/rite/Main_Page NTCIR-9 CrossLink CrossLingual Link Discovery Task http://ntcir.nii.ac.jp/CrossLink/ Open Topic Project Topics related to Data Warehousing, Business Intelligence, Data mining, Text mining, Web mining, Social Network Analysis, Link Mining.
NTCIR Project (NII Test Collection for IR Systems) http://research.nii.ac.jp/ntcir/ntcir-9/index.html
NTCIR-9 RITE Recognizing Inference in TExt @NTCIR9 http://artigas.lti.cs.cmu.edu/rite/Main_Page
NTCIR-9 CrossLink CrossLingual Link Discovery Task http://ntcir.nii.ac.jp/CrossLink/
Term Project Teams 5-7 人為一組 NTCIR Project 分組名單於 2011.02.22 (二) 課程下課時繳交 由班代統一收集協調分組名單 NTCIR Project NTCIR-9 RITE (Project 1 Teams) NTCIR-9 CrossLink (Project 2 Teams) Open Topic Project (Project 3 Teams) Topics related to Data Warehousing, Business Intelligence, Data mining, Text mining, Web mining, Social Network Analysis, Link Mining.
Contact Information 戴敏育 博士 (Min-Yuh Day, Ph.D.) 專任助理教授 淡江大學 資訊管理學系 電話:02-26215656 #2347 傳真:02-26209737 研究室:I716 (覺生綜合大樓) [Office Hour] 地址: 25137 新北市淡水區英專路151號 Email: myday@mail.im.tku.edu.tw 網址:http://mail.im.tku.edu.tw/~myday/