Estimating the Quality of a Selection of Scientific Papers Using a Collection of Short Texts
Author:
Publisher
Pleiades Publishing Ltd
Subject
Computer Vision and Pattern Recognition
Link
https://link.springer.com/content/pdf/10.1134/S1054661823030288.pdf
Reference21 articles.
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2. Iz Beltagy, Kyle Lo, and Arman Cohan, “SciBERT: A pretrained language model for scientific text,” in Proc. 2019 Conf. on Empirical Methods in Natural Language Processing and the 9th Int. Joint Conf. on Natural Language Processing (EMNLP-IJCNLP), Hong Kong, 2019 (Association for Computational Linguistics, 2019), pp. 3615–3620. https://doi.org/10.18653/v1/d19-1371
3. P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov, “Enriching word vectors with subword information,” Trans. Assoc. Comput. Linguist. 5, 135–146 (2016). https://doi.org/10.1162/tacl_a_00051
4. T. Dogan and A. K. Uysal, “On term frequency factor in supervised term weighting schemes for text classification,” Arabian J. Sci. Eng. 44, 9545–9560 (2019). https://doi.org/10.1007/s13369-019-03920-9
5. A comparison of term weighting schemes for text classification and sentiment analysis with a supervised variant of tf.idf;G. Domeniconi,2015
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