An architecture for parallel topic models

PVLDB, pp. 703-710, 2010.

Cited by: 440|Views41
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Abstract:

This paper describes a high performance sampling architecture for inference of latent topic models on a cluster of workstations. Our system is faster than previous work by over an order of magnitude and it is capable of dealing with hundreds of millions of documents and thousands of topics. The algorithm relies on a novel communication st...More

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