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» Continuous Processing of Preference Queries in Data Streams
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DASFAA
2007
IEEE
151views Database» more  DASFAA 2007»
13 years 10 months ago
The Tornado Model: Uncertainty Model for Continuously Changing Data
To support emerging database applications that deal with continuously changing (or moving) data objects (CCDOs), such as vehicles, RFIDs, and multi-stimuli sensors, one requires an...
Byunggu Yu, Seon Ho Kim, Shayma Alkobaisi, Wan D. ...
LCPC
2005
Springer
14 years 2 months ago
Code Transformations for One-Pass Analysis
With the growing popularity of streaming data model, processing queries over streaming data has become an important topic. Streaming data has received attention in a number of comm...
Xiaogang Li, Gagan Agrawal
ICDT
2010
ACM
219views Database» more  ICDT 2010»
14 years 6 months ago
Aggregate Queries for Discrete and Continuous Probabilistic XML
Sources of data uncertainty and imprecision are numerous. A way to handle this uncertainty is to associate probabilistic annotations to data. Many such probabilistic database mode...
Serge Abiteboul, T.-H Hubert Chan, Evgeny Kharlamo...
ICDE
2005
IEEE
173views Database» more  ICDE 2005»
14 years 10 months ago
Stabbing the Sky: Efficient Skyline Computation over Sliding Windows
We consider the problem of efficiently computing the skyline against the most recent N elements in a data stream seen so far. Specifically, we study the n-of-N skyline queries; th...
Xuemin Lin, Yidong Yuan, Wei Wang 0011, Hongjun Lu
PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 9 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...