Introduction
Potential topics will be announced in our twiki website (in
preparation); you are welcome to propose your own topics and recruit
your team members. Please think deeply and seriously. Team work
(2-3 students) is encouraged. Each project should have one of the
following goals:
- Empirical Survey: Study existing data mining and machine
learning techniques, implement/run and compare some of them for better understanding and
for possible improvement,
- Novel Application: Build a novel application with data mining
techniques applied,
- Original Research: Propose new data mining concepts,
formulations, or algorithms, aiming for publication.
Solid and original projects will be appreciated in this course.
Timeline
Proposal (Jan 25 2010):
Build a team, select a topic, and upload two-page proposal
including problem definition, datasets, task, and working plan, etc.
Midway Report (Feb 15 2010):
Upload two-page summary of what has been done.
Demo/Presentation (March 15/17 2010): Present
and/or demo projects in the class.
Final Report (March 17 2010): Submit a final report,
clearly describe the contribution of each team member.
Project Grade
Your project will be graded based on the following scheme:
- Project proposal: 10%
- Midway report: 20%
- Project presentation/demo: 30% (Student Voting)
- Project result/report: 40%
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