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Exploring Portuguese Word Embeddings for Discovering Lexical-Semantic Relations

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Computational Processing of the Portuguese Language (PROPOR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12037))

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Abstract

Word2vec-like word embeddings are known for kee** linguistic regularities and thus good for solving analogies. Following this, we explore such embeddings for Portuguese in the discovery of lexical-semantic relations, which can be used for augmenting lexical-semantic knowledge bases. In this exploratory approach, we tested different methods for discovering relations of different types and confirm that word embeddings can be used, at least, for suggesting new candidate relations.

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Notes

  1. 1.

    https://github.com/vecto-ai (December 2019).

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Author information

Authors and Affiliations

  1. ISEC, Polytechnic Institute of Coimbra, Coimbra, Portugal

    Tiago Sousa & Ana Alves

  2. CISUC, University of Coimbra, Coimbra, Portugal

    Ana Alves & Hugo Gonçalo Oliveira

  3. DEI, University of Coimbra, Coimbra, Portugal

    Hugo Gonçalo Oliveira

Authors
  1. Tiago Sousa
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  2. Ana Alves
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  3. Hugo Gonçalo Oliveira
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Corresponding author

Correspondence to Hugo Gonçalo Oliveira .

Editor information

Editors and Affiliations

  1. University of Évora, Evora, Portugal

    Paulo Quaresma

  2. University of Évora, Evora, Portugal

    Renata Vieira

  3. University of São Paulo, São Carlos, Brazil

    Sandra Aluísio

  4. University of Lisbon, Lisbon, Portugal

    Helena Moniz

  5. INESC-ID/ISCTE-IUL, Lisbon, Portugal

    Fernando Batista

  6. University of Évora, Evora, Portugal

    Teresa Gonçalves

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Sousa, T., Alves, A., Gonçalo Oliveira, H. (2020). Exploring Portuguese Word Embeddings for Discovering Lexical-Semantic Relations. In: Quaresma, P., Vieira, R., Aluísio, S., Moniz, H., Batista, F., Gonçalves, T. (eds) Computational Processing of the Portuguese Language. PROPOR 2020. Lecture Notes in Computer Science(), vol 12037. Springer, Cham. https://doi.org/10.1007/978-3-030-41505-1_38

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  • DOI: https://doi.org/10.1007/978-3-030-41505-1_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41504-4

  • Online ISBN: 978-3-030-41505-1

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