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
 101-1 
授課對象
 管理學院  資訊管理學系  
授課教師
 陳建錦 
課號
 IM5030 
課程識別碼
 725EU3410 
班次
  
學分
 3 
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
 管一204 
備註
 本課程以英語授課。
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/1011IRTM 
課程簡介影片
 
核心能力關聯
 核心能力與課程規劃關聯圖
課程大綱
為確保您我的權利,請尊重智慧財產權及不得非法影印
課程概述

This course will cover the concepts and algorithms of information retrieval and text mining. Theoretical topics, including term extraction, term weighting, vector space model, binary independence model, language model, IR system evaluations, naive bayes classification, Rocchio classification, kNN, k-means, HAC, PageRank, and HITS, will be presented in this course. Meanwhile, programming assignments and term projects will be given to help students understand the development of an IR system. 

課程目標
 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. Then, research topics, such as text classification and clustering, will be discussed to provide a comprehensive study on information retrieval and text mining. 
課程要求
 Programming language, data structure, and probability. 
預期每週課後學習時數
  
Office Hours
  
指定閱讀
  
參考書目
 Christopher D. Manning and Hinrich Schutze, Foundations of Statistical Natural
language Processing, The MIT Press, 1999.
William B. Frakes and Ricardo Baeza-Yates, Information Retrieval — Data
Structures and Algorithms, Prentice Hall, 1992.
Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Modern Information Retrieval,
Addison Wesley, 1999.
 
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>
Term Vocabulary  
Week 2
 9/18  Term Vocabulary <BR>
PAT Tree and Chinese Keyword Extraction <BR>
Programming Assignment 1 
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>
Programming Assignment 2<BR>
Evaluation in Information Retrieval 
Week 5
 10/09  Evaluation in Information Retrieval <BR>
Relevance Feedback and Query Expansion 
Week 6
 10/16  Relevance Feedback and Query Expansion <BR>
Probabilistic Information Retrieval
 
Week 7
 10/23  Probabilistic Information Retrieval <BR>
Language Models for Information Retrieval 
Week 8
 10/30  Language Models for Information Retrieval 
Week 9
 11/06  Midterm 
Week 10
 11/13  Language Models for Information Retrieval <BR>
Link Analysis 
Week 11
 11/20  Link Analysis <BR>
Text Classification and Naive Bayes 
Week 12
 11/27  Text Classification and Naive Bayes 
Week 13
 12/04  Vector Space Classification <BR>
(deliver one-page project proposal) 
Week 14
 12/11  Hierarchical Clustering 
Week 15
 12/18  Hierarchical Clustering<BR>
Flat Clustering 
Week 16
 12/25  Flat Clustering 
Week 17
 1/01  No class 
Week 18
 1/08  No class 
Week 19
 1/15  Project Demo