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» Clustering Genes Using Heterogeneous Data Sources
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BMCBI
2006
157views more  BMCBI 2006»
15 years 3 months ago
Determination of the minimum number of microarray experiments for discovery of gene expression patterns
Background: One type of DNA microarray experiment is discovery of gene expression patterns for a cell line undergoing a biological process over a series of time points. Two import...
Fang-Xiang Wu, W. J. Zhang, Anthony J. Kusalik
134
Voted
CIDM
2007
IEEE
15 years 9 months ago
Mining Subspace Correlations
— In recent applications of clustering such as gene expression microarray analysis, collaborative filtering, and web mining, object similarity is no longer measured by physical ...
Rave Harpaz, Robert M. Haralick
ER
2003
Springer
550views Database» more  ER 2003»
15 years 8 months ago
A UML Based Approach for Modeling ETL Processes in Data Warehouses
Data warehouses (DWs) are complex computer systems whose main goal is to facilitate the decision making process of knowledge workers. ETL (Extraction-Transformation-Loading) proces...
Juan Trujillo, Sergio Luján-Mora
DEXA
2007
Springer
154views Database» more  DEXA 2007»
15 years 9 months ago
Performance Oriented Schema Matching
Abstract. Semantic matching of schemas in heterogeneous data sharing systems is time consuming and error prone. Existing mapping tools employ semi-automatic techniques for mapping ...
Khalid Saleem, Zohra Bellahsene, Ela Hunt
AAAI
2011
14 years 3 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal