CSE 591 DATA MINING

(January 21- May 6, Spring 2003)

I hear, I forget; I see, I remember; I do, I understand. - Proverb

Your suggestions are most welcome. Please send email to hliu@asu.edu

Jan 23, 2003, Thur, Egeria Project and Other Related Image Mining Problems, Professor Patricia Foschi, San Francisco State University
Jan 28, 2003, Tues, cDNA Micoroarray Data Analysis (Note: the file is 8MB), Dominique Hoelzinger, TGen
Feb 4, 2003, Tues, Intelligent Driving Data Analysis, Dr. Kari Torkkola, email: Kari.Torkkola@motorola.com Motorola Human Interface Lab

Proposal (5%): (hard copy) due on Tues Feb 18, 2003.
Progress Report (5%): (hard copy) due on March 27, Thur. 5:00pm. Be brief. It is about the progress you have made and difficulties encountered with key references.
Presentation Slides (5%): (hard copy) due on April 24, Thur. (for about 5 minutes presentation in powerpoint, including title, problem statement, approach, and key results). Everybody should be prepared to present in class. Please also send your link or powerpoint files to Amit (amitm@asu.edu) as we will host all the slides there for presentation.
Final Report due on 5/6/02 by 5:00pm in hard copie (be concise and self contained) everything about your project with references.

Deadline for your hardcopy and email submission of the links to your presentation slides: 4/24 Thursday, 5:00pm. You can keep revising your softcopy after the hardcopy and the link are submitted.
The purpose of project presentation is to share the projects among us so that we know what others are doing. The project may be related to what you are doing or are interested in.
Selected students will have about 5 minutes for presentation and Q&A.
The slides should be accessible via Web. Please include the URL of your slides on the cover page.
Participation and presenting projects in class is a key element for class participation.

You're welcome to discuss with the instructor about your project ideas.

Self-proposing: solving a suitable problem from design to implementation
Establishing a mining environment for the course: installation and maintenance
Challenging problems and applications of data mining: identification and possible solutions

The length (or number of pages) is immaterial. In fact, a concise technical report is most preferred.
It is a concise and self-contained write-up such that another student can read it and repeat the work.
It should at a minimum include (1) the description of your project (2) the technical details (3) significance, usefulness, or impact (4) findings or results (5) future work, (6) important references.
For an implementation related project, you need to include a brief manual of how-to-use/development.
You should try to convey all your efforts on the project in the report in a simple manner.