Midterm
Presentations
CS522, Fall 2008
Monday 11/3 and Wednesday 11/5
Please upload your midterm presentation slides to CSNS.
One submission
from each group is sufficient. Note that file
uploading will be disabled automatically after 11:59PM
of the due date, so please
turn in your work on time.
Midterm presentations will be group presentations,
and each group should consist
of
three or four students. Each group must choose to present one of the
papers
listed in the Papers section.
Each group member must present
at least
10 minutes, and each
presentation must be at least 30 minutes and no more than 45 minutes.
Please let me know what paper you choose by Friday, October 24.
Paper selection
is firstcomefirstserve.
Your presentation should cover the following aspects of the
paper you selected:
 What problem did the authors try to solve? And why is the
problem interesting or important?
 What theories/algorithms/techniques have been proposed
before?
And why did they fall short of solving the problem (thus the
authors had to propose a new one)?
 Explanation of the proposed theory/algorithm/technique with examples.
 Evaluation or proof of the proposed
theory/algorithm/technique.
And here are some of the things I'll look for in each
presenter:
 Understanding of the whole paper, not just the part you
present.
 Presentation skills, i.e. the way you stand, talk, answer
questions, and interact
with the audience.
 Time management.
Total points for the midterm presentation is 20, half of which is for
the presentation as a whole, and the other half is for individual
performance.
[Schedule]

 Jonathan, Vahak, Yuri  Shared
Memory Parallelization of Data Mining Algorithms: Techniques,
Programming Interface, and Performance, by Ruoming Jin, Ge
Yang, and Gagan Agrawal.
 Peiling, Praweena, Hideyo  Integrating
Classification and Association Rule Mining (pdf), by Bing Liu,
Wynne Hsu, Yiming Ma.
[Papers]
 Optimization
of Frequent Itemset Mining on MultipleCore Processor, by Li
Liu, Eric Li, Yimin Zhang, Zhizhong Tang.
 Shared
Memory Parallelization of Data Mining Algorithms: Techniques,
Programming Interface, and Performance, by Ruoming Jin, Ge
Yang, and Gagan Agrawal.
 PrefixSpan:
Mining Sequential Patterns Efficiently by PrefixProjected Pattern
Growth, by Jian Pei, Jiawei Han, Behzad MortazaviAsl, Helen
Pinto, Qiming Chen Umeshwar Dayal MeiChun Hsu.
 Integrating
Classification and Association Rule Mining (pdf), by Bing Liu,
Wynne Hsu, Yiming Ma.
 Demographic
Prediction Based on User's Browsing Behavior, by Jian Hu,
HuaJun Zeng , Hua Li, Cheng Niu, Zheng Chen.