CS 33510: Data Mining and the Web
Spring 2006
Course Description
Data mining, an emerging field at the intersection of machine
learning, statistics, and databases, is broadly defined as finding
novel and interesting patterns in large amounts of data. In this
research-oriented course, we survey data-mining techniques and
applications, emphasizing the database perspective and web
applications. Major themes include association rules, web search and
mining, information extraction, and clustering. The course involves an independent
data-mining project.
Prerequisites
- CS 235 or CSPP 53001 or equivalent (databases)
- Strong programming skills
- CS 270 or CSPP 55001 or equivalent (algorithms)
Course Staff
Svetlozar Nestorov is the instructor for this course.
Contact Info
- Office: Ry275-A
- Email: evtimov at cs.uchicago.edu
- Phone: 2-3497
- Office hours: by appointment
Textboook
There is no required textbook. You may consider getting some of the
following books on data mining:
- Principles of Data Mining by David J. Hand, Heikki Mannila, Padhraic Smyth
- Data Mining: Concepts and Techniques by Jiawei Han, Micheline Kamber
Project
Project proposals are due in class on Thursday, April 13, 2006.
News Links
API and Data
Background Papers
Grading Policy
Grades will be based on class participation, presentations, and projects.
Papers
Association Rules
Web Search and Mining