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» Finding Frequent Items over General Update Streams
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IDA
2008
Springer
14 years 9 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»
15 years 1 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»
15 years 10 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»
15 years 9 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»
14 years 9 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