Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade

Roberta Rodrigues de Lima
* ,
Anita M. R. Fernandes
* ORCID logo ,
James Roberto Bombasar
,
Bruno Alves da Silva
ORCID logo ,
Paul Crocker
ORCID logo ,
Valderi Reis Quietinho Leithardt
*
Version 1 : Received: 20 November 2021 / Approved: 22 November 2021 / Online: 22 November 2021 (10:59:43 CET)

A peer-reviewed article of this Preprint also exists.

de Lima, R.R.; Fernandes, A.M.R.; Bombasar, J.R.; da Silva, B.A.; Crocker, P.; Leithardt, V.R.Q. An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade. Big Data Cogn. Comput. 2022, 6, 8. de Lima, R.R.; Fernandes, A.M.R.; Bombasar, J.R.; da Silva, B.A.; Crocker, P.; Leithardt, V.R.Q. An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade. Big Data Cogn. Comput. 2022, 6, 8.

Abstract

The classification of goods involved in international trade in Brazil is based on the Mercosur Common Nomenclature (NCM). The classification of these goods represents a real challenge due to the complexity involved in assigning the correct category codes especially considering the legal and fiscal implications of misclassification. This work focuses on the training of a classifier based on Bidirectional En-coder Representations from Transformers (BERT) for the tax classification of goods with NCM codes. In particular, this article presents results from using a specific Portuguese Language tuned BERT model as well results from using a Multilingual BERT. Experimental results justify the use of these models in the classification process and also that the language specific model has a slightly better performance.

Keywords

NCM classification; natural language processing; transformers; multilingual BERT; portuguese BERT; NLP; BERT

Subject

Engineering, Control and Systems Engineering

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.