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ICDM
2008
IEEE
120views Data Mining» more  ICDM 2008»
14 years 3 months ago
Predicting Future Decision Trees from Evolving Data
Recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. One approach to understa...
Mirko Böttcher, Martin Spott, Rudolf Kruse
DATAMINE
1998
106views more  DATAMINE 1998»
13 years 8 months ago
Discovering Robust Knowledge from Databases that Change
Many applications of knowledge discovery and data mining such as rule discovery for semantic query optimization, database integration and decision support, require the knowledge t...
Chun-Nan Hsu, Craig A. Knoblock
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
14 years 1 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
KDD
1995
ACM
135views Data Mining» more  KDD 1995»
14 years 5 days ago
Rough Sets Similarity-Based Learning from Databases
Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Xiaohua Hu, Nick Cercone
KDD
2008
ACM
110views Data Mining» more  KDD 2008»
14 years 9 months ago
Mining preferences from superior and inferior examples
Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing camp...
Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, ...