DAKE: Document-Level Attention for Keyphrase Extraction

Author:

Santosh Tokala Yaswanth Sri Sai,Sanyal Debarshi Kumar,Bhowmick Plaban Kumar,Das Partha Pratim

Publisher

Springer International Publishing

Reference31 articles.

1. Alzaidy, R., Caragea, C., Giles, C.L.: Bi-LSTM-CRF sequence labeling for keyphrase extraction from scholarly documents. In: Proceedings of The World Wide Web Conference, pp. 2551–2557. ACM (2019)

2. Beltagy, I., Cohan, A., Lo, K.: Scibert: pretrained contextualized embeddings for scientific text. arXiv preprint arXiv:1903.10676 (2019)

3. Berend, G.: Opinion expression mining by exploiting keyphrase extraction. In: Proceedings of the 5th International Joint Conference on Natural Language Processing. Asian Federation of Natural Language Processing (2011)

4. Caragea, C., Bulgarov, F.A., Godea, A., Gollapalli, S.D.: Citation-enhanced keyphrase extraction from research papers: a supervised approach. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1435–1446 (2014)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

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