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» Data streams: algorithms and applications
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PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 6 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 7 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias
ICDE
2006
IEEE
144views Database» more  ICDE 2006»
14 years 8 months ago
Approximately Processing Multi-granularity Aggregate Queries over Data Streams
Aggregate monitoring over data streams is attracting more and more attention in research community due to its broad potential applications. Existing methods suffer two problems, 1...
Shouke Qin, Weining Qian, Aoying Zhou
SODA
2004
ACM
173views Algorithms» more  SODA 2004»
13 years 8 months ago
Tabulation based 4-universal hashing with applications to second moment estimation
We show that 4-universal hashing can be implemented efficiently using tabulated 4-universal hashing for characters, gaining a factor of 5 in speed over the fastest existing method...
Mikkel Thorup, Yin Zhang
KDD
2003
ACM
192views Data Mining» more  KDD 2003»
14 years 7 months ago
Efficient elastic burst detection in data streams
Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
Yunyue Zhu, Dennis Shasha