Patent Classification for Business Strategy with BERT

Author:

Higashi Masaki,Utsumi Yoshimasa,Nakata Kazuhide

Publisher

Springer Nature Switzerland

Reference12 articles.

1. Benzineb, K., Guyot, J.: Automated patent classification. Curr. Challenges Pat. Inf. Retr. 29, 239–261 (2011)

2. Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: TProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 4171–4186 (2019)

3. Grover, A., Leskovec, J.: node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 855–864 (2016)

4. Kaiming, H., Xiangyu, Z., Shaoqing, R., Jian S.: deep residual learning for image recognition. Comput. Vis. Patt. Recog. 770–778 (2016)

5. Lee, J.-S., Hsiang, J.: PatentBERT: Patent classification with fine-tuning a pre-trained BERT model. World Pat. Inf. 61, 101965 (2020)

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