Horizontal implementation of expectation-maximization algorithm in SQL for performing clustering in very large databases

A method for performing cluster analysis inside a relational database management system. The method defines a plurality of tables for the storage of data points and Gaussian mixture parameters and executes a series of SQL statements implementing an Expectation-Maximization clustering algorithm to it...

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Main Authors ORDONEZ CARLOS, CEREGHINI PAUL M
Format Patent
LanguageEnglish
Published 02.09.2003
Edition7
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Abstract A method for performing cluster analysis inside a relational database management system. The method defines a plurality of tables for the storage of data points and Gaussian mixture parameters and executes a series of SQL statements implementing an Expectation-Maximization clustering algorithm to iteratively update the Gaussian mixture parameters stored within the tables.
AbstractList A method for performing cluster analysis inside a relational database management system. The method defines a plurality of tables for the storage of data points and Gaussian mixture parameters and executes a series of SQL statements implementing an Expectation-Maximization clustering algorithm to iteratively update the Gaussian mixture parameters stored within the tables.
Author ORDONEZ CARLOS
CEREGHINI PAUL M
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Snippet A method for performing cluster analysis inside a relational database management system. The method defines a plurality of tables for the storage of data...
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SubjectTerms CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
Title Horizontal implementation of expectation-maximization algorithm in SQL for performing clustering in very large databases
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