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» Efficiently Identifying Exploratory Rules' Significance
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APPINF
2003
13 years 8 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 7 days ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
BMCBI
2008
121views more  BMCBI 2008»
13 years 7 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
LDTA
2010
13 years 7 months ago
Faster ambiguity detection by grammar filtering
Real programming languages are often defined using ambiguous context-free grammars. Some ambiguity is intentional while other ambiguity is accidental. A good grammar development e...
H. J. S. Basten, Jurgen J. Vinju