Introduction
Potential topics will be announced here (in preparation); you are
welcome to propose your own topics and recruit your team members.
Please think deeply and seriously. Team work (2 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 20 2011):
Build a team, select a topic, and upload two-page proposal
including problem definition, datasets, task, and working plan, etc.
Midway Report (May 11 2011):
Upload two-page summary of what has been done.
Demo/Presentation (June 1/6 2011): Present
and/or demo projects in the class.
Final Report (June 8 2011): 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%
- Project presentation/demo: 40% (Student Voting)
- Project result/report: 50%
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