Topics Identification in a Corpus based on Transformers

Authors

  • Jorge Victor Carrera Trejo Investigador independiente
  • Rodrigo Cadena Martínez Universidad Tecnológica de México

DOI:

https://doi.org/10.13053/cys-26-3-4187

Keywords:

Bert, multilabel, topics, classification, transformers, spacy, comics

Abstract

Classifying a corpus of texts based on a set of classes using Transformers allows to build a model based on the words that contain the information, however, the model uses all the words in the training process and the order in which its found, but, which of these words are directly related to the topic of the texts? This work focuses on proposing a methodology that allows, using a multi-labeled corpus that contains the description of 1200 comics organized in 4 classes, to eliminate information that are not related to the topic, based on the identification of named entities and noun phrases, thereby generating a new corpus with which to train and validate a Transformer, using the macro accuracy measure as an evaluation measure, as a base case the macro accuracy value, obtained of the validation of a Transformer trained with the original data is proposed, demonstrating that when we using data related to the subject matter of the texts, the classification results are improved from 0.733 to 0.992

Downloads

Published

2022-08-28

Issue

Vol. 26 No. 3 (2022): 26(3) 2022

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.