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» Structure-aware sampling on data streams
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GRAPHICSINTERFACE
2009
13 years 5 months ago
Fast low-memory streaming MLS reconstruction of point-sampled surfaces
We present a simple and efficient method for reconstructing triangulated surfaces from massive oriented point sample datasets. The method combines streaming and parallelization, m...
Gianmauro Cuccuru, Enrico Gobbetti, Fabio Marton, ...
DMSN
2010
ACM
13 years 6 months ago
Facilitating fine grained data provenance using temporal data model
E-science applications use fine grained data provenance to maintain the reproducibility of scientific results, i.e., for each processed data tuple, the source data used to proce...
Mohammad Rezwanul Huq, Andreas Wombacher, Peter M....
EDBT
2008
ACM
103views Database» more  EDBT 2008»
14 years 7 months ago
A stratified approach to progressive approximate joins
Users often do not require a complete answer to their query but rather only a sample. They expect the sample to be either the largest possible or the most representative (or both)...
Wee Hyong Tok, Stéphane Bressan, Mong-Li Le...
APPROX
2011
Springer
197views Algorithms» more  APPROX 2011»
12 years 7 months ago
Periodicity and Cyclic Shifts via Linear Sketches
We consider the problem of identifying periodic trends in data streams. We say a signal a ∈ Rn is p-periodic if ai = ai+p for all i ∈ [n − p]. Recently, Erg¨un et al. [4] pr...
Michael S. Crouch, Andrew McGregor
ICDE
2009
IEEE
135views Database» more  ICDE 2009»
14 years 9 months ago
Forward Decay: A Practical Time Decay Model for Streaming Systems
Temporal data analysis in data warehouses and data streaming systems often uses time decay to reduce the importance of older tuples, without eliminating their influence, on the res...
Graham Cormode, Vladislav Shkapenyuk, Divesh Sriva...