Pachinko allocation: DAG-structured mixture models of topic correlations

ICML 2006 - Proceedings of the 23rd International Conference on Machine Learning

Volumn 2006, Issue , 2006, Pages 577-584

  Li, Wei ^a   McCallum, Andrew ^a  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIRECTED ACYCLIC GRAPH (DAG); DOCUMENT CLASSIFICATION; LATENT DIRICHLET ALLOCATION (LDA); PACHINKO ALLOCATION MODEL (PAM);

CLASSIFICATION (OF INFORMATION); CORRELATION METHODS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; TEXT PROCESSING;

DATA REDUCTION;

EID: 33749249041     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Blei, D., Griffiths, T., Jordan, M., & Tenenbaum, J. (2004). Hierarchical topic models and the nested Chinese restaurant process. In Advances in neural information processing systems 16.
2. Blei, D., & Lafferty, J. (2006). Correlated topic models. In Advances in neural information processing systems 18.
3. Blei, D., Ng, A., & Jordan, M. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022.
4. Chib, S. (1995). Marginal likelihood from the Gibbs output. Journal of the American Statistical Association.
5. Diggle, P., & Gratton, R. (1984). Monte Carlo methods of inference for implicit statistical models. Journal of the Royal Statistical Society.
6. Griffiths, T., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences (pp. 5228-5235).
7. Lawrie, D., Croft, W., & Rosenberg, A. (2001). Finding topic words for hierarchical summarization. Proceedings of SIGIR'01 (pp. 349-357).
8. Newton, M., & Raftery, A. (1994). Approximate Bayesian inference with the weighted likelihood bootstrap. Journal of the Royal Statistical Society.
9. Teh, Y., Jordan, M., Beal, M., & Blei, D. (2005). Hierarchical Dirichlet processes. Journal of the American Statistical Association.