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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
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...
ICDM
2007
IEEE
145views Data Mining» more  ICDM 2007»
14 years 1 months ago
Using Data Mining to Estimate Missing Sensor Data
Estimating missing sensor values is an inherent problem in sensor network applications; however, existing data estimation approaches do not apply well to the context of datastream...
Le Gruenwald, Hamed Chok, Mazen Aboukhamis
ICTAI
2003
IEEE
14 years 27 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
AUSAI
2003
Springer
14 years 25 days ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra