Topic Modeling for Short Texts via Adaptive P$\acute{o}$lya Urn Dirichlet Multinomial Mixture

Mark Junjie Li, Rui Wang, Jun Li, Xianyu Bao, Jueying He, Jiayao Chen, Lijuan He. Topic Modeling for Short Texts via Adaptive P$\acute{o}$lya Urn Dirichlet Multinomial Mixture. In Biao Luo, Long Cheng 0001, Zheng-Guang Wu, Hongyi Li 0001, Chaojie Li, editors, Neural Information Processing - 30th International Conference, ICONIP 2023, Changsha, China, November 20-23, 2023, Proceedings, Part XIV. Volume 1968 of Communications in Computer and Information Science, pages 364-376, Springer, 2023. [doi]

@inproceedings{LiWLBHCH23,
  title = {Topic Modeling for Short Texts via Adaptive P$\acute{o}$lya Urn Dirichlet Multinomial Mixture},
  author = {Mark Junjie Li and Rui Wang and Jun Li and Xianyu Bao and Jueying He and Jiayao Chen and Lijuan He},
  year = {2023},
  doi = {10.1007/978-981-99-8181-6_28},
  url = {https://doi.org/10.1007/978-981-99-8181-6_28},
  researchr = {https://researchr.org/publication/LiWLBHCH23},
  cites = {0},
  citedby = {0},
  pages = {364-376},
  booktitle = {Neural Information Processing - 30th International Conference, ICONIP 2023, Changsha, China, November 20-23, 2023, Proceedings, Part XIV},
  editor = {Biao Luo and Long Cheng 0001 and Zheng-Guang Wu and Hongyi Li 0001 and Chaojie Li},
  volume = {1968},
  series = {Communications in Computer and Information Science},
  publisher = {Springer},
  isbn = {978-981-99-8181-6},
}