1. AlSumait, L., Barbar, D., & Domeniconi, C. (2008). On-line lda: Adaptive topic models for mining text streams with applications to topic detection and tracking. In 2008 eighth IEEE international conference on data mining (pp. 3–12).
2. Asuncion, A., Welling, M., Smyth, P., & Teh, Y. W. (2009). On smoothing and inference for topic models. In Proceedings of the 25th conference on uncertainty in artificial intelligence, UAI ’09 (pp. 27–34). Arlington, Virginia, United States: AUAI Press.
3. Bengio, Y., Lamblin, P., Popovici, D., Larochelle, H., et al. (2007). Greedy layer-wise training of deep networks. Advances in Neural Information Processing Systems, 19, 153.
4. Bishop, C. M. (2006). Pattern recognition and machine learning (information science and statistics). New York: Springer.
5. Canini, K. R., Shi, L., & Griffiths, T. L. (2009). Online inference of topics with latent dirichlet allocation. In Proceedings of the international conference on artificial intelligence and statistics (pp. 65–72).