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» Data Quality Requirements Analysis and Modeling
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DKE
2008
109views more  DKE 2008»
15 years 26 days ago
Deterministic algorithms for sampling count data
Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...
Hüseyin Akcan, Alex Astashyn, Hervé Br...
180
Voted
JORS
2010
189views more  JORS 2010»
14 years 7 months ago
Monte Carlo scenario generation for retail loan portfolios
Monte Carlo simulation is a common method for studying the volatility of market traded instruments. It is less employed in retail lending, because of the inherent nonlinearities in...
J. L. Breeden, D. Ingram
DELOS
2007
15 years 2 months ago
Integration of Reliable Sensor Data Stream Management into Digital Libraries
Data Stream Management (DSM) addresses the continuous processing of sensor data. DSM requires the combination of stream operators, which may run on different distributed devices, ...
Gert Brettlecker, Heiko Schuldt, Peter M. Fischer,...
191
Voted
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
16 years 28 days ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...
132
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BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
15 years 19 days ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...