Open Access
Issue
MATEC Web of Conferences
Volume 22, 2015
International Conference on Engineering Technology and Application (ICETA 2015)
Article Number 01062
Number of page(s) 5
Section Information and Communication Technology
DOI https://doi.org/10.1051/matecconf/20152201062
Published online 09 July 2015
  1. Blei D M, Lafferty J D. 2009. Topic models. Text Mining: Classification, Clustering, and Applications, 10: 71. [CrossRef]
  2. Ramage D, Hall D, Nallapati R, et al. 2009. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, pp: 248–256.
  3. Mimno D, Li W, McCallum A. 2007. Mixtures of hier-archical topics with pachinko allocation. Proceedings of the 24th International Conference on Machine Learning. ACM, pp: 633–640.
  4. Li W., McCallum A. 2006. Pachinko allocation: DAG-structured mixture models of topic correlations. Proceedings of the 23rd International Conference on Machine Learning. ACM, pp: 577–584.
  5. Liu C, Wang F, Shi K, et al. 2014. Robust H∞ control for satellite attitude control system with uncertainties and additive perturbation. International Journal of Science, 1(2): 1–9.
  6. Blei D M. 2012. Probabilistic topic models. Communications of the ACM, 55(4): 77–84. [CrossRef]
  7. Andrzejewski D, Zhu X, Craven M. 2009. Incorporating domain knowledge into topic modeling via Dirichlet forest priors. Proceedings of the 26th Annual International Conference on Machine Learning. ACM, pp: 25–32.
  8. Liu C, Wang F. 2014. In-orbit estimation of inertia pa-rameters of target satellite after capturing the tracking satellite. Intelligent Control and Automation (WCICA), 2014 11th World Congress on. IEEE, pp: 3942–3947.
  9. Mimno D, McCallum A. Topic models conditioned on arbitrary features with dirichlet-multinomial regression. arXiv preprint arXiv:1206.3278, 2012.
  10. Teh Y W, Jordan M I, Beal M J, et al. 2006. Hierarchical dirichlet processes. Journal of the American Statistical Association, 101(476).
  11. Yu M, Wang J, Zhao X, et al. 2013. Research on PAM Probability topic model. Computer Science, 40(5): 1–7.
  12. Liu C, et al. 2014. Mass and mass center identification of target satellite after rendezvous and docking. Intelligent Control and Automation (WCICA), 2014 11th World Congress on. IEEE, pp: 5802–5807.
  13. Zhang C, Sun J. 2012. Large scale microblog mining using distributed MB-LDA. Proceedings of the 21st International Conference Companion on World Wide Web. ACM, pp: 1035–1042.
  14. Yu M, Zhou Z, et al. 2013. PAM-based microblog hot spot mining. Technique and Method, 32(15): 86–89.

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