1. Akujuobi, U., Zhang, X.: Delve: a dataset-driven scholarly search and analysis system. SIGKDD Explor. Newsl. 19(2), 36–46 (2017).
https://doi.org/10.1145/3166054.3166059
.
http://doi.acm.org/10.1145/3166054.3166059
2. Alexander, E., Kohlmann, J., Valenza, R., Witmore, M., Gleicher, M.: Serendip: topic model-driven visual exploration of text corpora. In: 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 173–182. IEEE (2014)
3. Blei, D.M., Lafferty, J.D., et al.: A correlated topic model of science. Ann. Appl. Stat. 1(1), 17–35 (2007)
4. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)
5. Cohan, A., Ammar, W., van Zuylen, M., Cady, F.: Structural scaffolds for citation intent classification in scientific publications. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies NAACL-HLT 2019, Minneapolis, MN, USA, June 2–7, 2019, Volume 1 (Long and Short Papers), pp. 3586–3596 (2019).
https://www.aclweb.org/anthology/N19-1361/