An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets.
Adam KirschMichael MitzenmacherAndrea PietracaprinaGeppino PucciEli UpfalFabio VandinPublished in: J. ACM (2012)
Keyphrases
- statistically significant
- frequent itemsets
- itemsets
- frequent itemset mining
- association rules
- mining frequent itemsets
- association rule mining
- mining algorithm
- attitudes toward
- learning styles
- concise representation
- control group
- statistical significance
- data structure
- frequent itemsets mining
- statistical tests
- data streams
- discovery of association rules
- pearson correlation
- deduction rules
- transactional databases
- frequent pattern mining
- itemset mining
- mining association rules
- transaction databases
- frequent patterns
- frequent itemset discovery
- minimum support
- frequent closed itemsets
- pruning strategy
- condensed representations
- closed itemsets
- uncertain data
- closed frequent itemsets
- frequent set mining
- apriori algorithm
- discovering association rules
- prefix tree
- data sets
- data mining
- real world