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SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
13 years 10 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
CINQ
2004
Springer
157views Database» more  CINQ 2004»
13 years 8 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
IJCNN
2007
IEEE
13 years 11 months ago
An Associative Memory for Association Rule Mining
— Association Rule Mining is a thoroughly studied problem in Data Mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the...
Vicente O. Baez-Monroy, Simon O'Keefe
SP
1999
IEEE
184views Security Privacy» more  SP 1999»
13 years 9 months ago
A Data Mining Framework for Building Intrusion Detection Models
There is often the need to update an installed Intrusion Detection System (IDS) due to new attack methods or upgraded computing environments. Since many current IDSs are construct...
Wenke Lee, Salvatore J. Stolfo, Kui W. Mok