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Published in:
2009 | OriginalPaper | Chapter
PLDA: Parallel Latent Dirichlet Allocation for Large-Scale Applications
Authors : Yi Wang, Hongjie Bai, Matt Stanton, Wen-Yen Chen, Edward Y. Chang
Published in: Algorithmic Aspects in Information and Management
Publisher: Springer Berlin Heidelberg
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This paper presents PLDA, our parallel implementation of Latent Dirichlet Allocation on MPI and MapReduce. PLDA smooths out storage and computation bottlenecks and provides fault recovery for lengthy distributed computations. We show that PLDA can be applied to large, real-world applications and achieves good scalability. We have released
MPI-PLDA
to open source at http://code.google.com/p/plda under the Apache License.