A Neural Topic Model Based on Variational Auto-Encoder for Aspect Extraction from Opinion Texts

Peng Cui, Yuanchao Liu, Bingquan Liu. A Neural Topic Model Based on Variational Auto-Encoder for Aspect Extraction from Opinion Texts. In Jie Tang 0001, Min-Yen Kan, Dongyan Zhao 0001, Sujian Li, Hongying Zan, editors, Natural Language Processing and Chinese Computing - 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9-14, 2019, Proceedings, Part I. Volume 11838 of Lecture Notes in Computer Science, pages 660-671, Springer, 2019. [doi]

@inproceedings{CuiLL19,
  title = {A Neural Topic Model Based on Variational Auto-Encoder for Aspect Extraction from Opinion Texts},
  author = {Peng Cui and Yuanchao Liu and Bingquan Liu},
  year = {2019},
  doi = {10.1007/978-3-030-32233-5_51},
  url = {https://doi.org/10.1007/978-3-030-32233-5_51},
  researchr = {https://researchr.org/publication/CuiLL19},
  cites = {0},
  citedby = {0},
  pages = {660-671},
  booktitle = {Natural Language Processing and Chinese Computing - 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9-14, 2019, Proceedings, Part I},
  editor = {Jie Tang 0001 and Min-Yen Kan and Dongyan Zhao 0001 and Sujian Li and Hongying Zan},
  volume = {11838},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-32233-5},
}