Efficient Vertical Mining of High Average-Utility Itemsets Based on Novel Upper-Bounds.
Tin C. TruongHai V. DuongBac LePhilippe Fournier-VigerPublished in: IEEE Trans. Knowl. Data Eng. (2019)
Keyphrases
- itemsets
- frequent itemsets
- upper bound
- sequential pattern mining algorithm
- mining algorithm
- association rule mining
- frequent itemset mining
- pruning strategy
- pattern mining
- high utility
- association rules
- emerging patterns
- mining association rules
- itemset mining
- mining of frequent itemsets
- data streams
- frequent patterns
- frequent pattern mining
- frequent item sets
- lower and upper bounds
- data structure
- interesting association rules
- mining frequent itemsets
- lower bound
- data mining algorithms
- anti monotone
- apriori algorithm
- transactional databases
- transaction databases
- closed frequent itemsets
- closed patterns
- transaction data
- frequent sets
- high utility itemsets
- maximal frequent itemsets
- discovering association rules
- interesting itemsets
- algorithms for mining association rules
- pattern discovery
- closed itemsets
- association patterns
- minimum support
- sequential pattern mining
- frequent closed itemsets
- interesting patterns
- high efficiency
- sequential patterns
- data mining
- data sets
- uncertain data
- logic programs
- multi dimensional