CS520, Spring 2007
Wednesday, June 6
Please upload your final presentation slides to CSNS.
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.
Final presentations will be group presentations, and
each group should consist
of two to four students. Each group must choose to present one of the
listed in the Papers section. Each group member must present
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 Wednesday, May 23.
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
And why did they fall short of solving the problem (thus the
authors had to propose a new one)?
- Description of the proposed theory/algorithm/technique.
- Evaluation or proof of the proposed
And here are some of the things I'll look for in each
Total points for the final presentation is 20, half of which is for
the presentation as a whole, and the other half is for individual
- Understanding of the whole paper, not just the part you
- Presentation skills, i.e. the way you stand, talk, answer
questions, and interact
with the audience.
- Time management.
Wednesday May 30, after lecture
1. Anuj, Bharat, Nidhi, and Sumathie - Mining
Patterns of Events in Students' Teamwork Data, by Judy Kay,
Nicolas Maisonneuve, Kalina Yacef, and Osmar R. Zaiane.
7:30PM - 10PM, Wednesday, June 6
2. Dan, Gail, Joan, and Tristan - SCORM
- specification, examples, tools and resources, and SCORM-compliance of
(in particular, .LRN,
ATutor, Moodle, and WebCT).
3. Chang-yin, Chao, and Yvon - Homepage
Live: Automatic Block Tracing for Web Personalization, by Jie
Han, Dingyi Han, Chenxi Lin, Hua-Jun Zeng, Zheng Chen, and Yong Yu.
4. Cheralyn, Kelly, and Nick - The Complex
Dynamics of Collaborative Tagging, by Harry Halpin, Valentin
Robu, and Hana Shepherd.
1. Google News
Personalization: Scalable Online Collaborative Filtering, by
Abhinandan Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram.
A Federated Repository for Searching and Querying Graph Structured Data,
by Andreas Harth, Jurgen Umbrich, Aidan Hogan, and Stefan Decker.
Mixed-Effects Modeling to Compare Different Grain-Sized Skill Models,
by Mingyu Feng, Neil Heffernan, Murali Mani, and Cristina Heffernan.