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ICDE
2005
IEEE
135views Database» more  ICDE 2005»
14 years 6 months ago
Finding (Recently) Frequent Items in Distributed Data Streams
We consider the problem of maintaining frequency counts for items occurring frequently in the union of multiple distributed data streams. Na?ive methods of combining approximate f...
Amit Manjhi, Vladislav Shkapenyuk, Kedar Dhamdhere...
SIGMOD
2008
ACM
164views Database» more  SIGMOD 2008»
14 years 4 months ago
Finding frequent items in probabilistic data
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or ...
Qin Zhang, Feifei Li, Ke Yi
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
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
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