Collective latent dirichlet allocation

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2008, Pages 1019-1024

  Shen, Zhi Yong ^a,b   Sun, Jun ^a,b   Shen, Yi Dong ^a  

^a INSTITUTE OF SOFTWARE   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; LATENT DIRICHLET ALLOCATION; LATENT DIRICHLET ALLOCATIONS;

EDUCATION; INFORMATION MANAGEMENT; MINING;

SOFTWARE AGENTS;

EID: 67049162741     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2008.75     Document Type: Conference Paper

References (15)

1. D.M. Blei and J. D. McAuliffe. Supervised topic models. In Proceedings of the 21th In Advances in Neural Information Processing Systems, 2007.
2. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. Journal of machine Learning Research, 3:993-1022, 2003.
3. P. Flahertya, G. Giaever, J. Kumm, M. I. Jordan, and A. P. Arkin. A latent variable model for chemogenomic profiling. bioinformatics, pages 3286-3293, 2005. (Pubitemid 41418443)
4. T. Griffiths. Gibbs sampling in the generative model of latent dirichlet allocation. www.psych.stanford.edu/gruffydd/cogsci02/lda.ps, 2002.
5. F. Li and P. Perona. A bayesian hierarchical model for learning natural scene categories. In In Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 524-531, 2005.
6. A. K. McCallum. Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering. http://www.cs.cmu.edu/mccallum/bow, 1996.
7. T. P. Minka. Estimating a dirichlet distribution. Technical report, MIT, 2000.
8. R. Raina, A. Battle, H. Lee, B. Packer, and A. Y. Ng. Selftaught learning: transfer learning from unlabeled data. In Proceedings of the Twenty-fourth International Conference on Machine Learning, page 759C766, 2007.
9. R. Raina, A. Y. Ng, and D. Koller. Constructing informative priors using transfer learning. In Proceedings of the Twentythird International Conference on Machine Learning, page 713C720, 2006.
10. M. M. Shafiei and E. E. Milios. Latent dirichlet coclustering. In Proceedings of the Sixth International Conference on Data Mining, pages 542 - 551, 2006.
11. M. Steyvers. Probabilistic topic models. Latent Semantic Analysis: A Road to Meaning, pages 427-448, 2007.
12. M. Steyvers, P. Smyth, and T. Griffiths. Probabilistic authortopic models for information discovery. In Proceedings of the 10th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 306-315, 2004. (Pubitemid 40114940)
13. Y. W. Teh, M. I. Jordan, and M. J. B. D. M. Blei. Hierarchical dirichlet processes. Journal of The American Statistical Association, 101:1566-1581, 2006.
14. X.Wang and A.McCallum. Topics over time: a non-markov continuous-time model of topical trends. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 424-433, 2006. (Pubitemid 44535539)
15. P. Wu and T. G. Dietterich. Improving svm accuracy by training on auxiliary data sources. In Proceedings of the 21-st International Conference on Machine Learning, pages 110-117, 2004.