課程資訊
課程名稱
資訊檢索
Information Retrieval 
開課學期
108-1 
授課對象
文學院  圖書資訊學系  
授課教師
唐牧群 
課號
LIS4012 
課程識別碼
106 47000 
班次
 
學分
3.0 
全/半年
半年 
必/選修
必帶 
上課時間
星期三6,7,8(13:20~16:20) 
上課地點
圖資視聽室 
備註
總人數上限:70人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1081LIS4012_ 
課程簡介影片
 
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課程概述

The course is designed to provide an introduction to the use, design and evaluation of information (IR) systems. It covers major components in the IR process such as information needs, search strategies, IR models and IR interaction. Students will acquire hand-on experiences with the design and evaluation of a digital library system. Special attention will be given to users’ information environment within which IR is situated. 

課程目標
To provide an introduction to the use, design and evaluation of information (IR) systems 
課程要求
待補 
預期每週課後學習時數
 
Office Hours
 
參考書目
Bell, S. S.(2006). Librarian's guide to online searching.
Bhavani, S. K. K. Drabenstott, D. Radev (2000). Towards a unified framework of IR tasks and strategies.
Manning, Raghavan, Schutze (2008). Introduction to Informaiton Retrieval. Cambridge.
Chowdhury, G.G. (2004), Introduction to modern information retrieval. London: Facet publishing.
William, H. R. (1996). Information retrieval : a health and biomedical perspective. New York: Springer-Verlag New York, Inc.
Salton & McGill (1983). Introduction to modern information retrieval. McGraw-Hill..
Growssman, and Frieder (2004). Information retrieval: algorithms and Heuristics
Belew, Richard K. (2000). Finding out about: a cognitive perspective on search engine technology and the WWW. Cambridge: Cambridge University Press.
O'Connor, B. (1996). Explorations in indexing and abstracting.
Evaluation of Web-Based Search Engines Using User-Effort Measures. Availableonline: http://libres.curtin.edu.au/libres13n2/tang.htm
Ian H. Witten, David Bainbridge (2003). How to Build a Digital Library, Amsterdam: Morgan Kaufmann Publishers. 
指定閱讀
待補 
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Search feature/command demo 
10% 
create and present a video demo that explains a search tactics or function available at PubMed database. See example 
2. 
Search engine or query performance comparison 
20% 
Each group will conduct an IR evaluation comparing three major web-based search engines (e.g. Google, Yahoo and Bing) based on three real search requests from user with real information needs. a. To obtain the search topics, interview three users (preferably graduate students or faculty members), each on one research topic they are interested in. Collect from each user: a search statement and associated query terms that you both agree best represent her information need. b. For each search topic, submit the queries on the user’s behalf to the three search engines you are testing. Collect the first 25 links from each of the three returned sets. c. Find out the degree of overlap among the three returned sets. d. Mix the non-duplicative (25X2, maximum) links together and strip the graphic cues. This is done so that the user will not be able to tell which search engine each link is from. e. For each link, marks its original and rank position. f. Present the URLs in Microsoft Word files that allow the users to examine the actual webpage by clicking on its hyperlink. Ask them to judge the relevance (topical as well as situational) of the pages based on a 0-4 scale (0 stands for not relevant at all; 4, very relevant). g. Create an EXCEL or SPSS data file to input the relevance scores. h. Compare the performance of the search engines based on 1) first 20 "full" precision, 2) search length "2" (i.e. the number of links the user has to go through to find two relevant documents, and 3) Discounted cumulated gain. i. Prepare a powerpoint slide on your findings and present them in the class. 
3. 
Digital library construction 
30% 
Each group will build a functional online digital library collaboratively using Joomla or Greenstone digital library (GSDL) open source software. DL_project_exampl1 DL_project_example2 The project consists of three components: the implantation of a digital collection on the topic of your own choosing, a written report (5-6 pages) and an oral presentation of the project at the end of the semester. The digital collection should include: a. A minimum of 60 documents representative of different document formats such as pdf, word, and html. b. An index structure that enables browsing of the collection c. The provision of fielded search The written report should: d. Explain the aim, purpose, intended users and their information needs of the collection. It is better that you come up with an institutional context (real or imaginary) for the use of the collection. e. Define your selection and indexing policies (human and machine indexing components; metadata structure) based on the aim and purpose stated above. f. Include a graphic presentation of the browsable index structure and the rationales behind your design (i.e. explain why you choose certain browsable facets and searchable fields to represent your collection) 
4. 
Wikipedia entry project 
10% 
Each student will create a Wikipedia entry at LIS_WIKI for a concept or theory covered in the class. To complete the assignment, First post your topic on the class discussion forum to claim your topic, then write a 2 - 4 pages explanatory texts that explain the defination, origin, and history of the concept. All the information you include in the entry has to be attributable to reliable sources. You MUST make rerference to as least one authoritative source such as "The Encyclopedia of Information Science and Technology," or "Encyclopedia of Library and Information Science". Also make sure you make proper citations to your source, see How to cite sources. 
5. 
Mid-term 
20% 
The exam is based on the lecture notes and readings. 
6. 
Class participation 
10% 
Attendance to all class sessions is mandatory. Your grade will be judged based on you attendance and participation in the class discussion. If you don’t get the chance to participate in the class, submit your comments or questions by emails or ceiba 
 
課程進度
週次
日期
單元主題
第1週
9/11  Introduction to syllabus
History of IR; data vs. information retrieval 
第2週
9/18  Advanced search with PubMed; introduction to search features with PubMed/Ovid/Ebsco/EMBASE 
第3週
9/25  Search strategies tactics ; PICO; factiva
Camtasia demo (laptop) 
第4週
10/02  Indexing exhaustivity vs. specificity
Automatic index basic (text analysis, term weighting) 
第5週
10/09  Relevance/IR evaluation/Class exercise 
第6週
10/16  Domain analysis demo/Citation indexing
Demo of ctext.org at the lab; TF*IDF tool 
第7週
10/23  IR models I: Boolean; term weighting and vector space model 
第8週
10/30  Relevance feedback and query expansion
(which should include search statement and queries) 
第9週
11/06  IR model II: Probability model,
Similarity measures 
第10週
11/13  Wordpress demo at computer lab 
第11週
11/20  Simulated search evaluation presentation 
第12週
11/27  Facet analysis and information architecture 
第13週
12/04  IR model: probabilistic and language models 
第14週
12/11  Lab session with your DL project 
第15週
12/18  DL assignment presentation 
第16週
12/25  Web search and link structure 
第17週
1/01  Final review 
第18週
1/08  Final exam sample