Evolutionary clustering by hierarchical dirichlet process with hidden markov state

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2008, Pages 658-667

  Xu, Tianbing ^a   Zhang, Zhongfei ^a   Yu, Philip S ^b   Long, Bo ^a  

^a State University of New York at Binghamton   (United States)

^b 1120 Science and Engineering Offices   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER NUMBERS; EFFECTIVE SOLUTION; EVOLUTIONARY CLUSTERING; HIERARCHICAL DIRICHLET PROCESS; HIERARCHICAL TRANSITION; MARKOV STATE; MARKOV STATE MODELS; SOCIAL NETWORK ANALYSIS; STATISTICAL MODELS;

EDUCATION; ELECTRIC NETWORK ANALYSIS; HIDDEN MARKOV MODELS; INFORMATION MANAGEMENT; MARKUP LANGUAGES; MINING; MODEL STRUCTURES;

CLUSTER ANALYSIS;

EID: 67049114684     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2008.24     Document Type: Conference Paper

References (27)

1. D. Aldous. Exchangeability and related topics. Ecole de Probabilites de Saint-Flour, (XIII):1-198, 1983.
2. C. Antoniak. Mixtures of dirichlet processes with applications to bayesian nonparametric problems. The Annals of Statistics, 2(6):1152-1174, 1974.
3. L. E. Baum, T. Petrie, G. Soules, and N.Weiss. A maximization technique occurring in the statistical analysis of probabilistic functions of markov chins. The Annals of Mathematical Statistics, 39(1):164-171, 1970.
4. M. J. Beal, Z. Ghahramani, and C. E. Rasmussen. The infinite hidden markov model. In NIPS 14, 2002.
5. D. Blackwell and J. MacQueen. Ferguson distributions via plya urn schemes. The Annals of Statistics, 1(2):353-355, 1973.
6. D. Blei and J. Lafferty. Dynamic topic models. In In Proceedings of the 23rd International Conference on Machine Learning, 2006.
7. D. Blei, A. Ng, and M. Jordan. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022, January 2003.
8. G. Casella and E. I. George. Explaining the gibbs sampler. The American Statistician, 46(3):167-174, Aug. 1992.
9. D. Chakrabarti, R. Kumar, and A. Tomkins. Evolutionary clustering. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 554-560, 2006. (Pubitemid 44535554)
10. Y. Chi, X. Song, D. Zhou, K. Hino, and B. L. Tseng. Evolutionary spectral clustering by incorporating temporal smoothness. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 153-162, 2007. (Pubitemid 350229202)
11. A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society, 39(1):1-38, 1977.
12. M. D. Escobar and M. West. Bayesian density estimation and inference using mixtures. The Annals of Statistics, 90:577-588, 1995.
13. T. S. Ferguson. A bayesian analysis of some nonparametric problems. The Annals of Statistics, 1(2):209-230, 1973.
14. E. B. Fox, E. B. Sudderth, M. I. Jordan, and A. S. Willsky. Developing a tempered hdp-hmm for systems with state persistence. Technical Report, Nov. 2007.
15. J. V. Gael, Y. Saatci, Y. W. Teh, and Z. Ghahramani. Beam sampling for the infinite hidden markov model. In 25th International Conference on Machine Learning, 2008.
16. T. L. Griffiths and M. Steyvers. Finding scientific topics. In Proceedings of the National Academy of Sciences, pages 5228-5235. Feb., 2004. (Pubitemid 38469131)
17. G. Heinrich. Parameter estimation for text analysis. Technical Report, 2004.
18. H. Ishwaran and L. F. JAMES. Gibbs sampling methods for stick-breaking priors. Journal of the American Statistical Association, 96(453):161-, 2001.
19. D. J. MacKay. Ensemble learning for hidden markov models. Technical Report, 1997.
20. K. Ni, L. Carin, and D. Dunson. Multi-task learning for sequential data via ihmms and the nested dirichlet process. In ICML, pages 689-696, 2007.
21. L. Rabiner. A tutorial on hidden markov models and selected applications inspeech recognition. In Proceedings of the IEEE, pages 257-286, 1989.
22. J. Sethuraman. A constructive definition of dirichlet priors. Statistica Sinica, 4:639-650, 1994.
23. A. Strehl and J. Ghosh. Cluster ensembles a knowledge reuse framework for combining partitionings. In Proceedings of AAAI, 2002.
24. L. Tang, H. Liu, J. Zhang, and Z. Nazeri. Community evolution in dynamic multi-mode networks. In KDD, pages 677- 685, 2008.
25. Y. Teh, M. B. M. Jordan, and D. Blei. Hierarchical dirichlet processes. Journal of the American Statistical Association, 101(476):1566-1581, 2007.
26. X. Wang and A. McCallum. Topics over time: A nonmarkov 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)
27. T. Xu, Z. Zhang, P. Yu, and B. Long. Dirichlet process based evolutionary clustering. In ICDM, 2008.