Topics over nonparametric time: A supervised topic model using bayesian nonparametric density estimation

CEUR Workshop Proceedings

Volumn 962, Issue , 2012, Pages 74-83

  Walker, Daniel D ^a   Seppi, Kevin ^a   Ringger, Eric K ^a  

^a 3361 TMCB   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MAXIMUM LIKELIHOOD ESTIMATION;

BETA DISTRIBUTIONS; DIRICHLET PROCESS MIXTURE; NON-PARAMETRIC; NON-PARAMETRIC DENSITY ESTIMATORS; NONPARAMETRIC DENSITY ESTIMATION; SYNTHETIC AND REAL DATA; TOPIC MODEL; TOPIC MODELING;

METADATA;

EID: 84922824202     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. David Aldous, Illdar Ibragimov, Jean Jacod, and David Aldous. Exchangeability and related topics. In cole d't de Probabilits de Saint-Flour XIII 1983, volume 1117 of Lecture Notes in Mathematics, pages 1-198. Springer Berlin/Heidelberg, 1985. 10.1007/BFb0099421.
2. Michael W. Berry, Murray Brown, and Ben Signer. 2001 topic annotated Enron email data set, 2007.
3. David M. Blei and Jon D. McAuliffe. Supervised topic models. In arXiv:1003.0783, March 2010.
4. J. Chang and D. Blei. Relational topic models for document networks. In Artificial Intelligence and Statistics, pages 81-88, 2009.
5. M.D. Escobar. Estimating normal means with a dirichlet process prior. Journal of the American Statistical Association, pages 268-277, 1994.
6. M.D. Escobar and M. West. Computing nonparametric hierarchical models. Practical nonparametric and semiparametric Bayesian statistics, pages 1-22, 1998.
7. S.M. Gerrish and D.M. Blei. Predicting legislative roll calls from text. In Proceedings of the 28th Annual International Conference on Machine Learning, number 11, 2011.
8. D. Lewis. Reuters-21578 text categorization test collection. http://www.research.att.com/~lewis, 1997.
9. A.Y. Lo. On a class of bayesian nonparametric estimates: I. density estimates. The Annals of Statistics, 12(1):351-357, 1984.
10. Andrew Kachites McCallum. MALLET: A machine learning for language toolkit. http://mallet.cs.umass.edu, 2002.
11. D. Mimno and A. McCallum. Topic models conditioned on arbitrary features with dirichletmultinomial regression. In Uncertainty in Artificial Intelligence, pages 411-418, 2008.
12. Xuerui Wang and Andrew McCallum. Topics over time: A non-markov continuous-time model of topical trends. In Proceedings of the 12th ACM SIGKDD international conference( KDD'06), Philadelphia, PA, August 2006.