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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Transformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERT
Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.01305105
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.
Abstract: Coherence evaluation is a problem related to the area of natural language processing whose complexity lies mainly in the analysis of the semantics and context of the words in the text. Fortunately, the Bidirectional Encoder Representation from Transformers (BERT) architecture can capture the aforemen-tioned variables and represent them as embeddings to perform Fine-tunings. The present study proposes a Second Fine-Tuned model based on BERT to detect inconsistent sentences (coherence evaluation) in scientific abstracts written in English/Spanish. For this purpose, 2 formal methods for the generation of inconsistent abstracts have been proposed: Random Manipulation (RM) and K-means Random Manipulation (KRM). Six experiments were performed; showing that performing Second Fine-Tuned improves the detection of inconsistent sentences with an accuracy of 71%. This happens even if the new retraining data are of different language or different domain. It was also shown that using several methods for generating inconsistent abstracts and mixing them when performing Second Fine-Tuned does not provide better results than using a single technique.
Keywords: Coherence evaluation; inconsistent sentences detec-tion; BERT; second fine-tuned
Anyelo-Carlos Gutierrez-Choque, Vivian Medina-Mamani, Eveling Castro-Gutierrez, Rosa Nunez-Pacheco and Ignacio Aguaded, “Transformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERT” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01305105
@article{Gutierrez-Choque2022,
title = {Transformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERT},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01305105},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01305105},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Anyelo-Carlos Gutierrez-Choque and Vivian Medina-Mamani and Eveling Castro-Gutierrez and Rosa Nunez-Pacheco and Ignacio Aguaded}
}
