Author:
Zhao Deji,Ning Bo,Song Shuangyong,Wang Chao,Chen Xiangyan,Yu Xiaoguang,Zou Bo
Publisher
Springer Nature Switzerland
Reference21 articles.
1. Abburi, H., Parikh, P., Chhaya, N., Varma, V.: Fine-grained multi-label sexism classification using a semi-supervised multi-level neural approach. Data Sci. Eng. 6(4), 359–379 (2021)
2. Banerjee, S., Akkaya, C., Perez-Sorrosal, F., Tsioutsiouliklis, K.: Hierarchical transfer learning for multi-label text classification. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (2019)
3. Borges, H.B., Nievola, J.C.: Multi-label hierarchical classification using a competitive neural network for protein function prediction. In: The 2012 International Joint Conference on Neural Networks (IJCNN), pp. 1–8. IEEE (2012)
4. Cerri, R., Barros, R.C., PLF de Carvalho, A.C., Jin, Y.: Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinform. 17(1), 1–24 (2016)
5. Cesa-Bianchi, N., Gentile, C., Tironi, A., Zaniboni, L.: Incremental algorithms for hierarchical classification. In: Advances in Neural Information Processing Systems, pp. 233–240 (2004)