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DAWAK
2006
Springer
13 years 8 months ago
An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams
Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that ...
Jia-Ling Koh, Shu-Ning Shin
ICDM
2007
IEEE
180views Data Mining» more  ICDM 2007»
13 years 11 months ago
Mining Frequent Itemsets in a Stream
We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency ove...
Toon Calders, Nele Dexters, Bart Goethals
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 5 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 5 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
IDA
2007
Springer
13 years 4 months ago
Approximate mining of frequent patterns on streams
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Claudio Silvestri, Salvatore Orlando