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Reasoning with Portuguese Word Embeddings

Authors Luís Filipe Cunha , J. João Almeida , Alberto Simões



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Author Details

Luís Filipe Cunha
  • Department of Informatics, University of Minho, Braga, Portugal
J. João Almeida
  • Centro ALGORITMI, Departamento de Informática, University of Minho, Braga, Portugal
Alberto Simões
  • 2Ai – School of Technology, IPCA, Barcelos, Portugal

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Luís Filipe Cunha, J. João Almeida, and Alberto Simões. Reasoning with Portuguese Word Embeddings. In 11th Symposium on Languages, Applications and Technologies (SLATE 2022). Open Access Series in Informatics (OASIcs), Volume 104, pp. 17:1-17:14, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/OASIcs.SLATE.2022.17

Abstract

Representing words with semantic distributions to create ML models is a widely used technique to perform Natural Language processing tasks. In this paper, we trained word embedding models with different types of Portuguese corpora, analyzing the influence of the models' parameterization, the corpora size, and domain. Then we validated each model with the classical evaluation methods available: four words analogies and measurement of the similarity of pairs of words. In addition to these methods, we proposed new alternative techniques to validate word embedding models, presenting new resources for this purpose. Finally, we discussed the obtained results and argued about some limitations of the word embedding models' evaluation methods.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Natural language processing
  • Computing methodologies → Machine learning
Keywords
  • Word Embeddings
  • Word2Vec
  • Evaluation Methods

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References

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