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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:

  1. Empirical Survey: Study existing data mining and machine learning techniques,  implement/run and compare some of them for better understanding and for possible improvement,
  2. Novel Application: Build a novel application with data mining techniques applied,
  3. Original Research: Propose new data mining concepts, formulations, or algorithms, aiming for publication.

Solid and original projects will be appreciated in this course.


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%