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Article

Towards Robust Word Embeddings for Noisy Texts

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Grupo COLE, Escola Superior de Enxeñaría Informática, Universidade de Vigo, 36310 Vigo, Spain
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Universidade da Coruña, CITIC. Grupo LyS, Departamento de Ciencias da Computación e Tecnoloxías da Información, 15071 A Coruña, Spain
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Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(19), 6893; https://doi.org/10.3390/app10196893
Received: 26 August 2020 / Revised: 21 September 2020 / Accepted: 28 September 2020 / Published: 1 October 2020
(This article belongs to the Section Computing and Artificial Intelligence)
Research on word embeddings has mainly focused on improving their performance on standard corpora, disregarding the difficulties posed by noisy texts in the form of tweets and other types of non-standard writing from social media. In this work, we propose a simple extension to the skipgram model in which we introduce the concept of bridge-words, which are artificial words added to the model to strengthen the similarity between standard words and their noisy variants. Our new embeddings outperform baseline models on noisy texts on a wide range of evaluation tasks, both intrinsic and extrinsic, while retaining a good performance on standard texts. To the best of our knowledge, this is the first explicit approach at dealing with these types of noisy texts at the word embedding level that goes beyond the support for out-of-vocabulary words. View Full-Text
Keywords: natural language processing; semantics; word embeddings; noisy texts; social media natural language processing; semantics; word embeddings; noisy texts; social media
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MDPI and ACS Style

Doval, Y.; Vilares, J.; Gómez-Rodríguez, C. Towards Robust Word Embeddings for Noisy Texts. Appl. Sci. 2020, 10, 6893. https://doi.org/10.3390/app10196893

AMA Style

Doval Y, Vilares J, Gómez-Rodríguez C. Towards Robust Word Embeddings for Noisy Texts. Applied Sciences. 2020; 10(19):6893. https://doi.org/10.3390/app10196893

Chicago/Turabian Style

Doval, Yerai, Jesús Vilares, and Carlos Gómez-Rodríguez. 2020. "Towards Robust Word Embeddings for Noisy Texts" Applied Sciences 10, no. 19: 6893. https://doi.org/10.3390/app10196893

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