Clustering association rules to build beliefs and discover unexpected patterns.
Danh Bui ThiPieter MeysmanKris LaukensPublished in: Appl. Intell. (2020)
Keyphrases
- association rules
- discovered patterns
- association rule discovery
- data mining techniques
- frequent patterns
- association rule mining
- data mining
- clustering algorithm
- similar patterns
- k means
- pattern extraction
- interesting patterns
- market basket data
- efficient discovery
- pattern discovery
- clustering method
- cluster analysis
- self organizing maps
- frequent itemsets
- market basket analysis
- itemsets
- transactional databases
- frequent sets
- transaction data
- association mining
- data points
- interestingness measures
- frequent itemset mining
- sequential pattern mining
- frequent pattern mining
- knowledge discovery
- multiple data streams
- formal concept analysis
- hierarchical clustering
- rule sets
- rules discovered
- decision making
- association patterns
- mining association rules
- mental states
- data clustering
- pattern mining
- unsupervised learning
- apriori algorithm
- data mining applications
- discovering interesting
- spectral clustering
- belief revision
- classification rules
- events occur
- indirect association