106學年第1學期課程綱要

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一、課程基本資料
開課序號 0539 課程學制
科目代碼 ISC8004 課程名稱 資料探勘技術與應用專題研究
英文名稱 Special Topics on Data Mining Techniques and Applications
全/半年 必/選修 選修
學分數 3.0 每週授課時數 正課時數: 3 小時
開課系級 圖資所(碩)碩博合開
先修課程
課程簡介 Data mining is the process of discovering interesting knowledge from large amounts of data stored either in databases, data warehouses, or other form of information repositories. The discovered knowledge may be known factual patterns, or may be knowledge, constraints, rules that have not yet been known. The goals of this course lie in introducing the concepts and framework of data mining, various data mining techniques, and data mining’s application in library and information science, and Internet.
課程目標 對應系所核心能力
1. The goals of this course lie in introducing the concepts and framework of data mining, various data mining techniques, and data mining’s application in library and information science, and Internet 碩士:
 2-1 具備問題分析及解決的能力
 2-3 具備規劃及評估資訊系統的能力
 4-1 以人為本,尊重知識,整合運用資訊科技與創新服務,促進知識之自由與有效使用。
博士:
 2-1 具備問題分析及解決的能力
 2-3 具備規劃及評估資訊系統的能力
 4-1 以人為本,尊重知識,整合運用資訊科技與創新服務,促進知識之自由與有效使用。

二、教學大綱
授課教師 吳怡瑾
教學進度與主題

 

Week

 

Topic

Ref.

1

9/11

Course overview

 

2

9/18

Introduction to Data Mining, Big Data Analytics

Getting to know you data

Chapter 1 &2

3

9/25

Main course: Getting to know you data & Data Preprocessing

 

4

10/02

中秋節

 

5

10/09

國慶日

 

6

10/16

Weka Introduction

Computer room

7

10/23

Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods I

Chapter 6

8

10/30

Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods I

Chapter 6

9

11/06

Computer room –WEKA II

Computer room

10

11/13

Midterm Project Demonstration and Discussion

Computer room

11

11/20

Classification and Clustering I

Chapter 8&9

12

11/27

Classification and Clustering II

Chapter 8&9

13

12/04

Computer room –WEKA III

Computer room

14

12/11

Computer room –WEKA III

Special Topic on Time-series Data Mining

Computer room

15

12/18

Special Topic on Recommendation and Data Mining in CRM

Handout

16

12/25

Final Project Presentation

Computer room

17

1/1

新年

 

18

1/8

Case studies of Data Mining in Library and Information Science

Handout


教學進度與主題附件

教學方法
方式 說明
講述法  
討論法  
實驗/實作 上機演練
專題研究  
評量方法
方式 百分比 說明
作業 35 %  
出席 15 %  
報告 15 %  
專題 35 %  
參考書目

JiaweiHanandMichelineKamber,"DataMining:ConceptsandTechniques,"3rded.

Englishversionwebsite:http://hanj.cs.illinois.edu/bk2/

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