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» Approximate Association Rule Mining
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ICDE
2008
IEEE
498views Database» more  ICDE 2008»
15 years 7 months ago
Injector: Mining Background Knowledge for Data Anonymization
Existing work on privacy-preserving data publishing cannot satisfactorily prevent an adversary with background knowledge from learning important sensitive information. The main cha...
Tiancheng Li, Ninghui Li
ADMA
2008
Springer
114views Data Mining» more  ADMA 2008»
14 years 2 months ago
Using Data Mining Methods to Predict Personally Identifiable Information in Emails
Private information management and compliance are important issues nowadays for most of organizations. As a major communication tool for organizations, email is one of the many pot...
Liqiang Geng, Larry Korba, Xin Wang, Yunli Wang, H...
CIDM
2007
IEEE
13 years 11 months ago
Mining the Students' Learning Interest in Browsing Web-Streaming Lectures
Web-Streaming lectures overcome the space and time barriers between learning and teaching, but bring higher requirements on the learning feedback of students when they browse lectu...
Long Wang 0002, Christoph Meinel
FIMI
2004
175views Data Mining» more  FIMI 2004»
13 years 9 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
14 years 1 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey