Highly scalable memory-efficient parallel LDA in a shared-nothing MPP database
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United States of America Patent
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Apr 19, 2016
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Sep 25, 2013
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Sep 25, 2013
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Abstract
Latent Dirichlet allocation (LDA) analysis on a dataset is performed on an MPP relational database by distributing subsets of said dataset to a plurality of segments of the MPP database, and performing LDA analysis in parallel on the respective subsets on the plurality of segments using Gibbs sampling. An object library on each segment provides executable objects of user defined functions that can be called by an SQL query when the query requires functionality provided by an object.
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