Using Neural Coherence Models to Assess Discourse Coherence

Author:

Azrou LiliaORCID,Oufaida HoudaORCID,Blache PhilippeORCID,Hamdine IsraaORCID

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Barzilay, R., Lapata, M.: Modeling local coherence: an entity-based approach. Comput. Linguist. 34(1), 1–34 (2008)

2. Berrar, D.: Cross-validation. In: Encyclopedia of Bioinformatics and Computational Biology, pp. 542–545. Academic Press, Oxford (2019)

3. Bird, S., Klein, E., Loper, E.: Natural language processing with Python: analyzing text with the natural language toolkit, chap. 5, pp. 179–219. O’Reilly Media (2009)

4. Brownlee, J.: Hyperparameter optimization with random search and grid search. Machine Learning Mastery (2020)

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

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