The Sensitivity of Latent Dirichlet Allocation for Information Retrieval

@inproceedings{Park2009TheSO,
  title={The Sensitivity of Latent Dirichlet Allocation for Information Retrieval},
  author={Laurence Anthony F. Park and Kotagiri Ramamohanarao},
  booktitle={ECML/PKDD},
  year={2009}
}
It has been shown that the use of topic models for Information retrieval provides an increase in precision when used in the appropriate form. Latent Dirichlet Allocation (LDA) is a generative topic model that allows us to model documents using a Dirichlet prior. Using this topic model, we are able to obtain a fitted Dirichlet parameter that provides the maximum likelihood for the document set. In this article, we examine the sensitivity of LDA with respect to the Dirichlet parameter when used… CONTINUE READING
7 Citations
10 References
Similar Papers

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…