Show simple item record

dc.contributor.authorGutiérrez Choque, Anyelo Carlos
dc.contributor.authorMedina Mamani, Vivian
dc.contributor.authorCastro Gutiérrez, Eveling
dc.contributor.authorNúñez Pacheco, Rosa
dc.contributor.authorAguaded, José Ignacio
dc.identifier.citationGutiérrez-Choque, A.-C., Medina-Mamani, V., Castro-Gutiérrez, E., Nuñez-Pacheco, R., & Aguaded, I. (2022). Transformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERT. In International Journal of Advanced Computer Science and Applications (Vol. 13, Issue 5). The Science and Information Organization.
dc.identifier.issn2156-5570 (electrónico)
dc.description.abstractCoherence 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 aforementioned 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.es_ES
dc.description.sponsorshipTo the Universidad Nacional de San Agust´ın de Arequipa for the funding granted to the project ”Transmedia, Gamification and Video games to promote scientific writing in Engineering students”, under Contract No. IBA-IB-38-2020-UNSA. We would like to thank to the ”Research Center, Transfer of Technologies and Software Development R+D+i” -CiTeSoft-EC-0003-2017-UNSA, for their collaboration in the use of their equipment and facilities, for the development of this research work.
dc.publisherThe Science and Information Organizationes_ES
dc.relation.isversionofPublisher’s version
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.subject.otherCoherence evaluationes_ES
dc.subject.otherInconsistent sentences detectiones_ES
dc.subject.otherSecond fine-tunedes_ES
dc.titleTransformer based Model for Coherence Evaluation of Scientific Abstracts: Second Fine-tuned BERTes_ES
dc.subject.unesco5701 Lingüística Aplicadaes_ES

Files in this item

This item appears in the following Collection(s)

Show simple item record

Atribución-NoComercial-SinDerivadas 3.0 España
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España

Copyright © 2008-2010. ARIAS MONTANO. Repositorio Institucional de la Universidad de Huelva
Contact Us | Send Feedback |