|
Submission Time |
Name |
Paper Title |
Topic# |
Date |
|
Tue Jan 18 18:00 CST 2000 |
Gretchen Schirag |
Comprehensible Knowledge Discovery: Gaining Insight from Data |
1 |
2/8/2000 |
|
Thu Jan 27 11:29 CST 2000 |
Adrian Kujaneck Agogino |
Visualization Techniques for Mining Large Databases: A Comparison |
1 |
2/8/2000 |
|
Tue Jan 25 20:43 CST 2000 |
Kaushik Anand Ghate |
Clustering Large Databases in Arbitrary Metric Spaces |
2 |
|
|
Wed Jan 26 11:35 CST 2000 |
Yousuf Bin Ahmed |
A Statistical Theory for Quantitative Association Rules |
3 |
|
|
Wed Jan 26 09:27 CST 2000 |
Austin Bingham |
Constraint-Based Rule Mining in Large, Dense Databases |
3 |
|
|
Tue Jan 25 16:30 CST 2000 |
David Brunke |
User Profiling in Personalization Applications through Rule Discovery and Validation |
3 |
|
|
Sun Jan 30 12:51 CST 2000 |
Ismail Syed |
Using Association Rules for Product Assortment Decisions: A Case Study |
3 |
|
|
Tue Feb 1 13:00 CST 2000 |
Vishal Mishra |
An Interval Classifier for Database Mining Applications |
4 |
|
|
Tue Feb 1 11:15 CST 2000 |
Roberto Francisco Zuniga |
On Support Vector Decision Trees for Database Marketing |
4 |
|
|
Tue Jan 25 09:59 CST 2000 |
Kung-Bin Sung |
SLIQ: A Fast Scalable Classifier for Data Mining |
4 |
|
|
Tue Jan 25 16:42 CST 2000 |
Arindam Banerjee |
Support vector classifiers: a first look |
4 |
|
|
Wed Jan 26 10:24 CST 2000 |
Tianping (Tim) Huang |
Density Biased Sampling: An Improved Method for Data Mining and Clustering |
5 |
|
|
Tue Jan 25 22:55 CST 2000 |
Jerome Froment-Curtil |
A Survey of Methods for Scaling Up Inductive Learning Algorithms |
6 |
|
|
Wed Jan 26 21:04 CST 2000 |
Srujana Merugu |
Scalable Parallel Data Mining for Association Rules |
6 |
|
|
Tue Feb 1 15:35 CST 2000 |
Yuan Qu |
Scaling EM (Expectation-Maximization) Clustering to Large Databases |
6 |
|
|
Wed Jan 26 17:52 CST 2000 |
Bertrand Portier |
The Effects of Training Set Size on Decision Tree Complexity |
6 |
|
|
Wed Jan 19 12:03 CST 2000 |
Dung Lam |
Empirical Analysis of Predictive Algorithms for Collaborative Filtering |
7 |
|
|
Tue Jan 25 15:28 CST 2000 |
Muthaiah Venkatachalam |
Searching the World Wide Web |
7 |
|
|
Mon Jan 31 13:17 CST 2000 |
Sanghoon Oh |
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases |
8 |
|
|
Wed Jan 26 15:20 CST 2000 |
Joe Sing Paul Chan |
Detecting Changes in Categorical Data: Mining Contrast Sets |
9 |
|
|
Tue Jan 25 17:28 CST 2000 |
Venkatesh Chandrasekaran |
Interactive Data Analysis: The Control Project |
9 |
|
|
Sun Jan 30 23:26 CST 2000 |
Anish Sam Jacob |
MetaCost: A General Method for Making Classifiers Cost-Sensitive |
9 |
|
|
Tue Jan 25 21:28 CST 2000 |
Arvind Siotia |
Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem |
9 |
|
|
Mon Jan 31 20:08 CST 2000 |
Alextair D. Mascarenhas |
Statistics and Data Mining Techniques for Lifetime Value Modeling |
9 |
|
|
Tue Feb 1 17:00 CST 2000 |
David C. James |
The Impact of Changing Populations on Classifier Performance |
9 |
|
|
Tue Jan 25 15:43 CST 2000 |
Xiaoyun Yang |
What Makes Patterns Interesting in Knowledge Discovery Systems |
9 |
|