An efficient rigorous approach for identifying statistically significant frequent itemsets.
Adam KirschMichael MitzenmacherAndrea PietracaprinaGeppino PucciEli UpfalFabio VandinPublished in: PODS (2009)
Keyphrases
- statistically significant
- frequent itemsets
- itemsets
- frequent itemset mining
- mining frequent itemsets
- association rules
- association rule mining
- attitudes toward
- mining algorithm
- statistical significance
- control group
- data structure
- frequent itemsets mining
- learning styles
- data streams
- frequent closed itemsets
- frequent patterns
- discovery of association rules
- concise representation
- itemset mining
- pearson correlation
- closed itemsets
- mining association rules
- frequent set mining
- interesting patterns
- uncertain data
- transaction databases
- transactional databases
- condensed representations
- minimum support
- data mining techniques
- frequent itemset discovery
- frequent sets
- logic programs
- frequent pattern mining
- statistical tests
- fp tree
- pruning strategy
- closed frequent itemsets
- males and females
- data analysis
- sliding window