Ranking Association Rules by Clustering Through Interestingness.
Veronica Oliveira de CarvalhoDavi Duarte de PaulaMateus Violante PachecoWaldeilson Eder dos SantosRenan de PaduaSolange Oliveira RezendePublished in: MICAI (1) (2017)
Keyphrases
- association rules
- market basket data
- association rule mining
- classification rules
- knowledge discovery
- data mining
- k means
- clustering algorithm
- mining association rules
- data mining techniques
- high dimensional data
- discovered rules
- numerical attributes
- clustering method
- interestingness measures
- association mining
- categorical data
- itemsets
- association rules mining
- interesting rules
- frequent patterns
- apriori algorithm
- mining algorithm
- heterogeneous information networks
- formal concept analysis
- data mining tasks
- ranking functions
- link analysis
- data clustering
- ranking algorithm
- self organizing maps
- frequent itemsets
- web search
- pattern discovery
- fuzzy clustering
- learning to rank
- spectral clustering
- rule sets
- cluster analysis
- outlier detection
- content similarity
- feature selection