plda is a parallel C++ implementation of Latent Dirichlet Allocation (LDA) (1). We are expecting to present a highly optimized parallel implemention of the Gibbs sampling algorithm for the training/inference of LDA (2). The carefully designed architecture is expected to support extensions of this algorithm.
If you wish to publish any work based on plda, please cite our paper as: Yi Wang, Hongjie Bai, Matt Stanton, Wen-Yen Chen and Edward Y. Chang, PLDA: Parallel Latent Dirichlet Allocation for Large-scale Applications. Proc. of 5th International Conference on Algorithmic Aspects in Information and Management (AAIM), San Francisco, CA, June 2009. Software available at http://code.google.com/p/plda.
If you have any questions, please visit http://groups.google.com/group/plda
The bibtex format is
@InProceedings{
plda,
author = {Yi Wang and Hongjie Bai and Matt Stanton and Wen-Yen Chen and Edward Y. Chang},
title = {PLDA: Parallel Latent Dirichlet Allocation for Large-scale Applications},
year = {2009},
booktitle = {Proc. of 5th International Conference on Algorithmic Aspects in Information and Management},
note = {Software available at \url{http://code.google.com/p/plda}}
}References:
(1) PLDA: Parallel Latent Dirichlet Allocation for Large-scale Applications. Yi Wang, Hongjie Bai, Matt Stanton, Wen-Yen Chen, and Edward Y. Chang. AAIM 2009.
http://plda.googlecode.com/files/aaim.pdf(2) Latent Dirichlet Allocation, Blei et al., JMLR (3), 2003.
http://www.cs.princeton.edu/~blei/papers/BleiNgJordan2003.pdf(3) Finding scientific topics, Griffiths and Steyvers, PNAS (101), 2004.
http://www.pnas.org/content/101/suppl.1/5228.full.pdf(4) Fast collapsed gibbs sampling for latent dirichlet allocation, Porteous et al., KDD 2008.
http://portal.acm.org/citation.cfm?id=1401960(5) Distributed Inference for Latent Dirichlet Allocation, Newman et al., NIPS 2007.
http://books.nips.cc/papers/files/nips20/NIPS2007_0672.pdf
Papers using plda code:
(5) Collaborative Filtering for Orkut Communities: Discovery of User Latent Behavior. Wen-Yen Chen et al., WWW 2009.
http://www.cs.ucsb.edu/~wychen/publications/fp365-chen.pdf