An Itemset-Driven Cluster-Oriented Approach to Extract Compact and Meaningful Sets of Association Rules.
Claudio Haruo YamamotoMaria Cristina Ferreira de OliveiraMagaly Lika FujimotoSolange Oliveira RezendePublished in: ICMLA (2007)
Keyphrases
- association rules
- association rule mining
- frequent itemsets
- itemsets
- mining algorithm
- data mining
- knowledge discovery
- data mining techniques
- association mining
- mining association rules
- condensed representations
- minimum support
- clustering algorithm
- apriori algorithm
- interestingness measures
- market basket data
- formal concept analysis
- data points
- rule sets
- frequent sets
- association rules mining
- data streams
- databases
- data driven
- mining frequent itemsets
- frequent item sets
- data structure
- frequent patterns
- frequent itemset mining
- data clustering
- associative classification
- itemset mining
- hierarchical structure
- interesting rules
- interesting patterns
- discovered rules
- hierarchical clustering