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» Approximate Counts and Quantiles over Sliding Windows
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DIS
2009
Springer
14 years 2 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...
ICDE
2006
IEEE
178views Database» more  ICDE 2006»
14 years 8 months ago
Characterizing and Exploiting Reference Locality in Data Stream Applications
In this paper, we investigate a new approach to process queries in data stream applications. We show that reference locality characteristics of data streams could be exploited in ...
Feifei Li, Ching Chang, George Kollios, Azer Besta...
SIGMOD
2008
ACM
138views Database» more  SIGMOD 2008»
14 years 7 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
Rainer Gemulla, Wolfgang Lehner
DASFAA
2010
IEEE
193views Database» more  DASFAA 2010»
13 years 5 months ago
A Simple, Yet Effective and Efficient, Sliding Window Sampling Algorithm
Sampling streams of continuous data with limited memory, or reservoir sampling, is a utility algorithm. Standard reservoir sampling maintains a random sample of the entire stream a...
Xuesong Lu, Wee Hyong Tok, Chedy Raïssi, St&e...
BMCBI
2006
118views more  BMCBI 2006»
13 years 7 months ago
Microarray image analysis: background estimation using quantile and morphological filters
Background: In a microarray experiment the difference in expression between genes on the same slide is up to 103 fold or more. At low expression, even a small error in the estimat...
Anders Bengtsson, Henrik Bengtsson