Factors affecting the performance of parallel mining of minimal unique itemsets on diverse architectures.
David J. HaglinKenneth R. MayesAnna M. ManningJohn FeoJohn R. GurdMark ElliotJohn A. KeanePublished in: Concurr. Comput. Pract. Exp. (2009)
Keyphrases
- factors affecting
- itemsets
- frequent itemsets
- mining algorithm
- association rule mining
- itemset mining
- mining association rules
- frequent itemset mining
- association rules
- pattern mining
- data structure
- frequent patterns
- emerging patterns
- frequent item sets
- association patterns
- high utility itemsets
- frequent pattern mining
- interesting patterns
- data mining algorithms
- data streams
- minimum support
- transactional databases
- association rule mining algorithms
- interesting association rules
- frequent sets
- sequential pattern mining algorithm
- transaction data
- transaction databases
- closed patterns
- mining frequent itemsets
- closed itemsets
- interesting itemsets
- mining of frequent itemsets
- mining high utility itemsets
- apriori algorithm
- closed frequent itemsets
- frequent closed itemsets
- interestingness measures
- mining frequent
- maximal frequent
- maximal frequent itemsets
- sequential patterns
- knowledge discovery
- anti monotone
- data sets