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IEEEHPCS
2010
13 years 6 months ago
Discovering closed frequent itemsets on multicore: Parallelizing computations and optimizing memory accesses
The problem of closed frequent itemset discovery is a fundamental problem of data mining, having applications in numerous domains. It is thus very important to have efficient par...
Benjamin Négrevergne, Alexandre Termier, Je...
ICDM
2008
IEEE
121views Data Mining» more  ICDM 2008»
14 years 2 months ago
Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams
Efficient mining of high utility itemsets has become one of the most interesting data mining tasks with broad applications. In this paper, we proposed two efficient one-pass algor...
Hua-Fu Li, Hsin-Yun Huang, Yi-Cheng Chen, Yu-Jiun ...
DAWAK
2005
Springer
14 years 1 months ago
A Decremental Algorithm for Maintaining Frequent Itemsets in Dynamic Databases
Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management. Most existing data-mining alg...
Shichao Zhang, Xindong Wu, Jilian Zhang, Chengqi Z...
IDA
2002
Springer
13 years 7 months ago
Optimization of association rule mining queries
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Baptiste Jeudy, Jean-François Boulicaut
DKE
2008
124views more  DKE 2008»
13 years 7 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios