Using Bloom Filters for Mining Top-k Frequent Itemsets in Data Streams.
Younghee KimKyung Soo ChoJae Yeol YoonIee Joon KimUngmo KimPublished in: STA (2011)
Keyphrases
- bloom filter
- frequent itemsets
- data streams
- frequent closed itemsets
- minimum support
- data structure
- reservoir sampling
- itemsets
- space efficient
- frequent pattern mining
- closed itemsets
- frequent itemset mining
- mining frequent itemsets
- frequent itemsets mining
- sliding window
- mining algorithm
- association rule mining
- record linkage
- mining frequent closed itemsets
- streaming data
- mining association rules
- uncertain data
- itemset mining
- transactional databases
- concept drift
- concise representation
- data sets
- frequent patterns
- stream data
- discovery of association rules
- association rules
- condensed representations
- closed frequent itemsets
- interesting patterns
- membership queries
- real world
- frequent itemset discovery
- frequent set mining
- index structure
- apriori algorithm
- stream mining
- data stream mining
- data mining algorithms
- transaction databases
- pruning strategy
- mining of frequent itemsets
- limited memory
- frequent sets