九十八學年度 第二學期 資工碩
G-5151-15821 網際網路資料探勘 Web Data Mining
Web Data Mining (Spring, 2010)
Time and Place:
Time: Tue. E1, E2, E3
Classroom: SF305
Teacher:
徐嘉連
E-mail:
Phone: ext. 3817
Office: 聖言樓 SF618 室
Office Hours: Mon. 78
TA:
簡維萱
E-mail: xxx＠xxx.com
Phone: ext. 3893
Office: SF650
Office Hours: xxxx
Description:
Discuss concepts and algorithms of data mining. Especially focus on research issues of multimedia data mining, web data mining, and searching engine.
Course outline:
I. Introduction II. Data Mining
1. Association rules and sequential patterns 2. Supervised learning
3. Unsupervised learning III. Web Mining
1. Information retrieval and web search 2. Link analysis
3. Opinion mining 4. Web usage mining
IV. Search engine and information retrieval 1. Processing text
2. Ranking with indexes 3. Social search
Requirements:
None, but …
1. Multimedia database 2. data mining
3. database
九十八學年度 第二學期 資工碩
G-5151-15821 網際網路資料探勘 Web Data Mining
4. pattern recognition / machine learning / …
Textbook:
1. Bing Liu, Web Data Mining: Exploring Hyperlinks, Content, and Usage Data, Springer-Verlag, 2007.
2. W.B. Croft, D. Metzler, and T. Strohman, Search Engines:
Information Retrieval in Practice, Pearson, 2010.
Reference:
1. Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers; 2nd edition (March, 2006)
2. Perner, P., Data mining on multimedia data, Springer (LNCS 2558), 2002.
3. Hewlett, W. and E. Selfridge-Field (ed.), The Virtual Score:
Representation, Retrieval and Restoration (Computing in Musicology: 12). The MIT Press, 2001.
4. Hewlett, W. and E. Selfridge-Field (ed.), Melody Similarity:
Concepts, Procedures, and Applications (Computing in Musicology:
11). The MIT Press, 1998.
5. ISMIR: 2009, 2008, 2007, 2006, 2005, 2004, 2003, …
6. Faloutsos, Christos, Searching Multimedia Databases by Content, Kluwer Academic Publishers, 1996.
7. Pang-Ning Tan, Michael Steinbach, and Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006, (ISBN: 0-321-32136-7) 8. Li, Ze-Nian and Mark S. Drew, Fundamentals of Multimedia,
Pearson Prentice Hall, 2004.
9. Mitra, S. and Acharya, T., Data mining: Multimedia, soft computing, and bioinformatics, Wiley, 2003.
10. Witten, I. H., E. Frank, Data Mining, Morgan Kaufmann Publishers, Inc., 1999.
Online resource:
1. ACM Digital Library: ACM-MM, CIKM, SIGIR, SIGMOD, SIGKDD, … 2. IEEE Xplor (IEL): trans. on multimedia, ICME, ICDE, trans. on
knowledge and engineering, …
3. ISMIR: 2008, 2007, 2006, 2005, 2004, 2003, … 4. VLDB, …
九十八學年度 第二學期 資工碩
G-5151-15821 網際網路資料探勘 Web Data Mining
Course web:
1. http://www.csie.fju.edu.tw/~alien 2. icanXP.
Evaluation and grading:
Exercises, midterm, final (optional), term project and presentation (once or twice).
(如果不交 project，扣考、期末成績以零分計。)
Note:
No cheating, no plagiarism.
Turn off cellular phones in class.
各項成績與點名紀錄等，均會公布在課程網站上。在公布之後的一週內，
可提出複查。逾期，不受理。
在期末考的前一週，請再次核對各項成績。
點名四次未到（含四次），學期總成績以零分計。
請尊重智慧財產權、不要使用非法軟體、不要非法影印書籍
Resource:
http://www-sal.cs.uiuc.edu/~hanj/bk2/
http://www-users.cs.umn.edu/~kumar/dmbook/projects.htm
http://www-users.cs.umn.edu/~kumar/dmbook/resources.htm
http://www-users.cs.umn.edu/~kumar/dmbook/index.php#item4
Term project:
內容/進度，包括：
1. project 題目及構想
2. demo & oral presentation
3. final written report (minimal number of papers: four, at least 10 references, must have your OWN words, including introduction, background, analysis, figures, results, and conclusions. Format:
IEEE two-columns conference proceeding format)
缺繳上述三項中任一項者，將視為缺交 project，扣考、期末成績以零分計
report 在 demo 時一併繳交
