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» Mining Frequent Itemsets Using Genetic Algorithm
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PAKDD
2000
ACM
128views Data Mining» more  PAKDD 2000»
15 years 1 months ago
Efficient Detection of Local Interactions in the Cascade Model
Detection of interactions among data items constitutes an essential part of knowledge discovery. The cascade model is a rule induction methodology using levelwise expansion of a la...
Takashi Okada
SDM
2007
SIAM
190views Data Mining» more  SDM 2007»
14 years 11 months ago
AC-Framework for Privacy-Preserving Collaboration
The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. Increasing security concerns have led to a surge in w...
Wei Jiang, Chris Clifton
ADMA
2005
Springer
189views Data Mining» more  ADMA 2005»
15 years 3 months ago
Parallel Genetic Algorithm and Parallel Simulated Annealing Algorithm for the Closest String Problem
In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments sho...
Xuan Liu, Hongmei He, Ondrej Sýkora
ECEASST
2006
305views more  ECEASST 2006»
14 years 9 months ago
The ParMol Package for Frequent Subgraph Mining
Mining for frequent subgraphs in a graph database has become a popular topic in the last years. Algorithms to solve this problem are used in chemoinformatics to find common molecul...
Thorsten Meinl, Marc Wörlein, Olga Urzova, In...
MLDM
2007
Springer
15 years 3 months ago
Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...
Trevor Parsons, John Murphy, Patrick O'Sullivan