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» Mining Spatial Gene Expression Data for Association Rules
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BMCBI
2006
169views more  BMCBI 2006»
13 years 8 months ago
Finding biological process modifications in cancer tissues by mining gene expression correlations
Background: Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This techno...
Giacomo Gamberoni, Sergio Storari, Stefano Volinia
KDD
1998
ACM
183views Data Mining» more  KDD 1998»
14 years 24 days ago
Mining Generalized Association Rules and Sequential Patterns Using SQL Queries
Database integration of mining is becoming increasingly important with tile installation of larger and larger data warehouses built around relational database technology. Most of ...
Shiby Thomas, Sunita Sarawagi
DATAMINE
1998
126views more  DATAMINE 1998»
13 years 8 months ago
An Extension to SQL for Mining Association Rules
Data mining evolved as a collection of applicative problems and efficient solution algorithms relative to rather peculiar problems, all focused on the discovery of relevant infor...
Rosa Meo, Giuseppe Psaila, Stefano Ceri
ICFCA
2007
Springer
14 years 13 days ago
A New and Useful Syntactic Restriction on Rule Semantics for Tabular Datasets
Different rule semantics have been successively defined in many contexts such as implications in artificial intelligence, functional dependencies in databases or association rules...
Marie Agier, Jean-Marc Petit
ICPR
2006
IEEE
14 years 9 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen