Discovery Projects - Grant ID: DP0345901

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP0345901

Funding Status
Closed

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Funded Activity Summary

Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.

Funded Activity Details

Start Date: 01-01-2003

End Date: 31-12-2007

Funding Scheme: Discovery Projects

Funding Amount: $165,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Neural Networks, Genetic Alogrithms And Fuzzy Logic | Applied Statistics | Artificial Intelligence and Image Processing | Pattern Recognition

ANZSRC Socio-Economic Objective (SEO)

Application packages | Computer software and services not elsewhere classified | Mathematical sciences |

Other Keywords

Application packages | Applied Statistics | Artificial Intelligence and Image Processing | Computer software and services not elsewhere classified | Mathematical sciences | Neural Networks, Genetic Alogrithms And Fuzzy Logic | Pattern Recognition

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