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» Maintaining variance and k-medians over data stream windows
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DASFAA
2010
IEEE
193views Database» more  DASFAA 2010»
14 years 9 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...
CIKM
2009
Springer
15 years 6 months ago
Evaluating top-k queries over incomplete data streams
We study the problem of continuous monitoring of top-k queries over multiple non-synchronized streams. Assuming a sliding window model, this general problem has been a well addres...
Parisa Haghani, Sebastian Michel, Karl Aberer
SIGMOD
2006
ACM
238views Database» more  SIGMOD 2006»
15 years 12 months ago
Continuous monitoring of top-k queries over sliding windows
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in convent...
Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Pa...
ISAAC
2004
Springer
117views Algorithms» more  ISAAC 2004»
15 years 5 months ago
Adaptive Spatial Partitioning for Multidimensional Data Streams
We propose a space-efficient scheme for summarizing multidimensional data streams. Our sketch can be used to solve spatial versions of several classical data stream queries effici...
John Hershberger, Nisheeth Shrivastava, Subhash Su...
INFFUS
2008
175views more  INFFUS 2008»
14 years 11 months ago
Adaptive optimization of join trees for multi-join queries over sensor streams
Data processing applications for sensor streams have to deal with multiple continuous data streams with inputs arriving at highly variable and unpredictable rates from various sour...
Joseph S. Gomes, Hyeong-Ah Choi