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» Finding Frequent Items over General Update Streams
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IDA
2008
Springer
13 years 5 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
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
13 years 9 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
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 6 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
PODS
2006
ACM
134views Database» more  PODS 2006»
14 years 5 months ago
Finding global icebergs over distributed data sets
Finding icebergs ? items whose frequency of occurrence is above a certain threshold ? is an important problem with a wide range of applications. Most of the existing work focuses ...
Qi Zhao, Mitsunori Ogihara, Haixun Wang, Jun Xu
JIIS
2008
133views more  JIIS 2008»
13 years 5 months ago
Maintaining frequent closed itemsets over a sliding window
In this paper, we study the incremental update of Frequent Closed Itemsets (FCIs) over a sliding window in a high-speed data stream. We propose the notion of semi-FCIs, which is to...
James Cheng, Yiping Ke, Wilfred Ng