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» Automated dimensionality reduction of data warehouses
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GRC
2010
IEEE
13 years 6 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
BMCBI
2005
118views more  BMCBI 2005»
13 years 4 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner
ICASSP
2010
IEEE
13 years 5 months ago
Swift: Scalable weighted iterative sampling for flow cytometry clustering
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
Iftekhar Naim, Suprakash Datta, Gaurav Sharma, Jam...
PKDD
2005
Springer
125views Data Mining» more  PKDD 2005»
13 years 10 months ago
A Propositional Approach to Textual Case Indexing
Abstract. Problem solving with experiences that are recorded in text form requires a mapping from text to structured cases, so that case comparison can provide informed feedback fo...
Nirmalie Wiratunga, Robert Lothian, Sutanu Chakrab...
GIS
2003
ACM
14 years 5 months ago
Indexing of network constrained moving objects
With the proliferation of mobile computing, the ability to index efficiently the movements of mobile objects becomes important. Objects are typically seen as moving in two-dimensi...
Dieter Pfoser, Christian S. Jensen