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DATAMINE
2006
230views more  DATAMINE 2006»
13 years 4 months ago
Mining top-K frequent itemsets from data streams
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
13 years 8 months ago
Mining top-k frequent items in a data stream with flexible sliding windows
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
Hoang Thanh Lam, Toon Calders
PODS
2006
ACM
217views Database» more  PODS 2006»
14 years 4 months ago
A simpler and more efficient deterministic scheme for finding frequent items over sliding windows
In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
Lap-Kei Lee, H. F. Ting
IDA
2008
Springer
13 years 4 months ago
Mining frequent items in a stream using flexible windows
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...
Toon Calders, Nele Dexters, Bart Goethals
DIS
2009
Springer
13 years 11 months ago
A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams
Some challenges in frequent pattern mining from data streams are the drift of data distribution and the computational efficiency. In this work an additional challenge is considered...
Fabio Fumarola, Anna Ciampi, Annalisa Appice, Dona...