Online Belief Propagation for Topic Modeling

@article{Zeng2012OnlineBP,
  title={Online Belief Propagation for Topic Modeling},
  author={Jia Zeng and Zhi-Qiang Liu and Xiao-Qin Cao},
  journal={ArXiv},
  year={2012},
  volume={abs/1210.2179}
}
The batch latent Dirichlet allocation (LDA) algorithms play important roles in probabilistic topic modeling, but they are not suitable for processing big data streams due to high time and space compleixty. Online LDA algorithms can not only extract topics from big data streams with constant memory requirements, but also detect topic shifts as the data stream flows. In this paper, we present a novel and easy-to-implement online belief propagation (OBP) algorithm that infers the topic… CONTINUE READING

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