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» Mining Frequent Itemsets from Uncertain Data
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CVPR
2008
IEEE
14 years 9 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
ICDM
2007
IEEE
169views Data Mining» more  ICDM 2007»
13 years 11 months ago
Efficient Discovery of Frequent Approximate Sequential Patterns
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
AEI
2007
91views more  AEI 2007»
13 years 8 months ago
MICF: An effective sanitization algorithm for hiding sensitive patterns on data mining
Data mining mechanisms have widely been applied in various businesses and manufacturing companies across many industry sectors. Sharing data or sharing mined rules has become a tr...
Yu-Chiang Li, Jieh-Shan Yeh, Chin-Chen Chang
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 9 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
VLDB
2005
ACM
180views Database» more  VLDB 2005»
14 years 1 months ago
Cache-conscious Frequent Pattern Mining on a Modern Processor
In this paper, we examine the performance of frequent pattern mining algorithms on a modern processor. A detailed performance study reveals that even the best frequent pattern min...
Amol Ghoting, Gregory Buehrer, Srinivasan Parthasa...