과제정보
연구 과제 주관 기관 : 동의대학교
참고문헌
- Blei, D. M., Andrew, Y. N., Michael, I. J. (2003). Latent Dirichlet allocation, The Journal of Machine Learning Research, 3, 993-1022.
- Blei, D., Laerty, J. (2006). Dynamic topic models, In International Conference on Machine Learning, 113-120, New York, ACM.
- Blei, D., Laerty, J. (2007). A correlated topic model of science, Annals of Applied Statistics, 1(1), 17-35. https://doi.org/10.1214/07-AOAS114
- Blei, D., McAulie, J. (2007). Supervised topic models, In Neural Information Processing Systems.
- Choi, J., Jin, S., Choi, J. (2017). A study on differences of aspect of report by news media using text mining analysis, Journal of the Korean Data Analysis Society, 19, 5(B), 2509-2522. (in Korean).
- Griffiths, T. L., Steyvers, M. (2004). Finding scientific topics, Proceedings of the National Academy of Sciences of the United States of America, 101, 5228-5235.
- Grun, B., Hornik, K. (2011). Topicmodels: an R package for fitting topic models, Journal of Statistical Software, 40(13), 1-30.
- Kim, J. S., Jin, S. H. (2013). A study on the application of opinion mining based on big data, Journal of the Korean Data Analysis Society, 15, 101-114. (in Korean).
- Oh, M., Kim, S., Kang, C., Kim, K. K., Choi, S., Jeon, Y. (2016). Topics classification of applications using the latent Dirichlet allocation model, Journal of the Korean Data Analysis Society, 18, 4(B), 1895-1903. (in Korean).
- Woo, S. W., Chang, Y. J. (2016). An analysis of FOMC statements by text mining methods, Journal of the Korean Data Analysis Society, 18, 179-188. (in Korean).