Grounded Theory-Driven Knowledge Production Features Mining: One Empirical Study Based on Big Data Technology

Hao Xu, Yiyang Li, Mulan Wang, Yufang Peng, Qinwei Chen, Pengcheng Liu 0006, Yijing Li. Grounded Theory-Driven Knowledge Production Features Mining: One Empirical Study Based on Big Data Technology. In Yuan Tian 0003, Tinghuai Ma, Qingshan Jiang, Qi Liu, Muhammad Khurram Khan, editors, Big Data and Security - 4th International Conference, ICBDS 2022, Xiamen, China, December 8-12, 2022, Proceedings. Volume 1796 of Communications in Computer and Information Science, pages 493-511, Springer, 2022. [doi]

@inproceedings{XuLWPC0L22,
  title = {Grounded Theory-Driven Knowledge Production Features Mining: One Empirical Study Based on Big Data Technology},
  author = {Hao Xu and Yiyang Li and Mulan Wang and Yufang Peng and Qinwei Chen and Pengcheng Liu 0006 and Yijing Li},
  year = {2022},
  doi = {10.1007/978-981-99-3300-6_35},
  url = {https://doi.org/10.1007/978-981-99-3300-6_35},
  researchr = {https://researchr.org/publication/XuLWPC0L22},
  cites = {0},
  citedby = {0},
  pages = {493-511},
  booktitle = {Big Data and Security - 4th International Conference, ICBDS 2022, Xiamen, China, December 8-12, 2022, Proceedings},
  editor = {Yuan Tian 0003 and Tinghuai Ma and Qingshan Jiang and Qi Liu and Muhammad Khurram Khan},
  volume = {1796},
  series = {Communications in Computer and Information Science},
  publisher = {Springer},
  isbn = {978-981-99-3300-6},
}