Concept Shift Detection for Frequent Itemsets from Sliding Windows over Data Streams.
Jia-Ling KohChing-Yi LinPublished in: DASFAA Workshops (2009)
Keyphrases
- data streams
- frequent itemsets
- sliding window
- mining frequent itemsets
- change detection
- itemsets
- closed frequent itemsets
- frequent itemset mining
- association rule mining
- streaming data
- mining algorithm
- concept drift
- concise representation
- stream data
- sensor networks
- data distribution
- space efficient
- frequent closed itemsets
- sensor data
- discovery of association rules
- data sets
- fixed size
- maximal frequent itemsets
- mining maximal frequent itemsets
- interesting patterns
- high speed data streams
- frequent itemsets mining
- continuous queries
- emerging patterns
- transactional databases
- mining data streams
- association rules
- itemset mining
- mining association rules
- walsh hadamard transform
- minimum support
- condensed representations
- data structure
- uncertain data
- frequent patterns
- mining frequent patterns
- multi dimensional
- anomaly detection
- stream mining
- database
- variable size
- limited memory
- pruning strategy