課程資訊
課程名稱
資訊檢索與文字探勘導論
Introduction to Information Retrieval and Text Mining 
開課學期
107-1 
授課對象
學程  知識管理學程  
授課教師
陳建錦 
課號
IM5030 
課程識別碼
725 U3410 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二2,3,4(9:10~12:10) 
上課地點
管二103 
備註
本課程中文授課,使用英文教科書。知識管理學程系統領域選修課程。
限學士班三年級以上
總人數上限:25人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1071IRTM 
課程簡介影片
 
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課程概述

THE COURSE IS AIMED AT GRADUATE STUDENTS OR SENIOR UNDERGRADUATE STUDENTS WHO ARE INTERESTED IN INFORMATION RETRIEVAL AND TEXT MINING. THE FIRST PART OF THE COURSE WILL COVER THE BASICS OF INFORMATION RETRIEVAL, INCLUDING THE MANNER OF DOCUMENT REPRESENTATION, TERM WEIGHTING, AND EVALUATION METRICS USED TO COMPARE INFORMATION RETRIEVAL SYSTEMS. THEN, RESEARCH TOPICS, SUCH AS TEXT CLASSIFICATION AND CLUSTERING, WILL BE DISCUSSED TO PROVIDE A COMPREHENSIVE STUDY ON INFORMATION RETRIEVAL AND TEXT MINING. 

課程目標
待補 
課程要求
待補 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
 
參考書目
CHRISTOPHER D. MANNING, PRABHAKAR RAGHAVAN, AND HINRICH SCHUTZE, "INTRODUCTION TO INFORMATION RETRIEVAL," CAMBRIDGE UNIVERSITY PRESS. 2008. 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
Week 1
9/11  Syllabus<BR>
The Term Vocabulary 
Week 2
9/18  The Term Vocabulary <BR>
PAT Tree and Chinese Keyword Extraction 
Week 3
9/25  PAT Tree and Chinese Keyword Extraction<BR>
Scoring, Term Weighting and the Vector Space Model 
Week 4
10/02  Scoring, Term Weighting and the Vector Space Model<BR>
Evaluation in Information Retrieval 
Week 5
10/09  Evaluation in Information Retrieval <BR>
Probabilistic Information Retrieval 
Week 6
10/16  Probabilistic Information Retrieval <BR>
Language Models for Information Retrieval 
Week 7
10/23  Language Models for Information Retrieval 
Week 8
10/30  Link Analysis 
Week 9
11/06  midterm 
Week 10
11/13  Text Classification and Naïve Bayes 
Week 11
11/20  Text Classification and Naïve Bayes<BR>
Vector Space Classification 
Week 12
11/27  Vector Space Classification 
Week 13
12/04  Hierarchical Clustering<BR>
(delivery of term project proposal) 
Week 14
12/11  Hierarchical Clustering 
Week 15
12/18  Flat Clustering 
Week 16
12/25  Flat Clustering<BR>
Incremental Clustering<BR>
Topic Detection and Tracking 
Week 17
1/01  Holiday (no class) 
Week 18
1/8  final 
Week 19
1/15  term project presentation