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
(2-5 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 (April 14 2009):
Build a team, select a topic, and upload two-page proposal
including problem definition, datasets, task, and working plan,
Milestone I, Milestone II, etc.
Milestone I (May 5 2009):
Upload two-page summary of what has been done and explain if the
Milestone I target is achieved or not.
Milestone II (May 21 2009): Upload
two-page summary of what has been done between Milestones I and II, and explain if
the Milestone II
target is achieved or not.
Demo/Presentation (June 09/11 2009): Present
and/or demo projects in the class.
Final Report (June 11 2009): 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%
- Milestone I 15%
- Milestone II 15%
- Project presentation/demo: 30% (Student Voting)
- Project result/report: 30%
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