Web Mining Seminar (Spring 2008)

Instructor: Prof. Brian D. Davison
davison(at)cse.lehigh.edu
http://www.cse.lehigh.edu/~brian/

Time/Location: MWF 11:10-12:00 in Maginnes 113

Introduction: The accessibility and ubiquity of content on the WWW has changed how we perceive information. In this seminar, we will consider how to extract and discover information within the Web and from how we use the Web. Expected topics will include web search, web usage mining, text mining, information extraction, link analysis, and more.
This course will focus on reading and presenting papers related to mining the world-wide web, and will include a semester-long project. Paper and presentation critiques will be required, and course participation will be evaluated.

Objectives: To become proficient at reading technical papers; to gain knowledge of important current web mining research; to gain experience presenting technical material; to learn to write critical reviews of research papers; to explore a research project in some depth and write a technical paper summarizing that work.

Prerequisite: One or more of CSE345/445 WWW Search Engines, CSE347/447 Data Mining, CSE430 Textual Data Mining, or CSE326/426 Pattern Recognition.

Examinations: Midterm; no final exam

Textbook(s): Required: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, by Bing Liu (Springer, 2007). Recommended: Data Mining: Practical Machine Learning Tools and Techniques, 2nd Ed, by Witten and Frank (Morgan Kaufmann, 2005). We will also read and discuss significant and recent papers.

Useful Links: Syllabus, Schedule, WEKA

Announcements

1/18 - Possible project ideas are now online. (Note that this page is only accessible from Lehigh.)

This page is http://www.cse.lehigh.edu/~brian/course/webmining/
Last revised: 18 January 2008.

Instructor:	Prof. Brian D. Davison davison(at)cse.lehigh.edu http://www.cse.lehigh.edu/~brian/
Time/Location:	MWF 11:10-12:00 in Maginnes 113
Introduction:	The accessibility and ubiquity of content on the WWW has changed how we perceive information. In this seminar, we will consider how to extract and discover information within the Web and from how we use the Web. Expected topics will include web search, web usage mining, text mining, information extraction, link analysis, and more. This course will focus on reading and presenting papers related to mining the world-wide web, and will include a semester-long project. Paper and presentation critiques will be required, and course participation will be evaluated.
Objectives:	To become proficient at reading technical papers; to gain knowledge of important current web mining research; to gain experience presenting technical material; to learn to write critical reviews of research papers; to explore a research project in some depth and write a technical paper summarizing that work.
Prerequisite:	One or more of CSE345/445 WWW Search Engines, CSE347/447 Data Mining, CSE430 Textual Data Mining, or CSE326/426 Pattern Recognition.
Examinations:	Midterm; no final exam
Textbook(s):	Required: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, by Bing Liu (Springer, 2007). Recommended: Data Mining: Practical Machine Learning Tools and Techniques, 2nd Ed, by Witten and Frank (Morgan Kaufmann, 2005). We will also read and discuss significant and recent papers.
Useful Links:	Syllabus, Schedule, WEKA