1. Luling, X., Zixi, W., Yeqiu, C., Yichao, W., Di, Z.: COVID-19 literature mining and analysis research. In: 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022. IEEE, pp. 1045–1052 (2022)
2. Sirajzade(B), J., Bouvry, P., Schommer, C.: Deep mining COVID-19 literature. In: Florez, H., Gomez, H. (eds.) Applied Informatics (ICAI 2022), vol. 1643, pp. 121–133. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-19647-8_9
3. Parlina, A., Ramli, K., Murfi, H.: Exposing emerging trends in smart sustainable city research using deep autoencoders-based fuzzy c-means. Sustain. 13, 1–28 (2021)
4. Van Nguyen, T., Cong Pham, H., Nhat Nguyen, M., Zhou, L., Akbari, M.: Data-driven review of blockchain applications in supply chain management: key research themes and future directions. Int. J. Prod. Res. (2023)
5. Sindhusuta, S., Chi, S.W., Derrible, S.: A text-mining-based approach for conducting literature review of selected Meshfree methods. Comput. Assist. Methods Eng. Sci. 28, 265–290 (2021)