J. C. Bailón-Elvira, Manuel J. Cobo, Enrique Herrera-Viedma, Antonio Gabriel López-Herrera. Latent Dirichlet Allocation (LDA) for improving the topic modeling of the official bulletin of the spanish state (BOE). In Enrique Herrera-Viedma, Yong Shi, Daniel Berg, James M. Tien, Francisco Javier Cabrerizo, Jianping Li 0001, editors, Proceedings of the 7th International Conference on Information Technology and Quantitative Management, ITQM 2019, Information Technology and Quantitative Management based on Artificial Intelligence, November 3-6, 2019, Granada, Spain. Volume 162 of Procedia Computer Science, pages 207-214, Elsevier, 2019. [doi]
@inproceedings{Bailon-ElviraCH19,
title = {Latent Dirichlet Allocation (LDA) for improving the topic modeling of the official bulletin of the spanish state (BOE)},
author = {J. C. Bailón-Elvira and Manuel J. Cobo and Enrique Herrera-Viedma and Antonio Gabriel López-Herrera},
year = {2019},
doi = {10.1016/j.procs.2019.11.277},
url = {https://doi.org/10.1016/j.procs.2019.11.277},
researchr = {https://researchr.org/publication/Bailon-ElviraCH19},
cites = {0},
citedby = {0},
pages = {207-214},
booktitle = {Proceedings of the 7th International Conference on Information Technology and Quantitative Management, ITQM 2019, Information Technology and Quantitative Management based on Artificial Intelligence, November 3-6, 2019, Granada, Spain},
editor = {Enrique Herrera-Viedma and Yong Shi and Daniel Berg and James M. Tien and Francisco Javier Cabrerizo and Jianping Li 0001},
volume = {162},
series = {Procedia Computer Science},
publisher = {Elsevier},
}