<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Vector models based on word embeddings are an indispensable part of advanced Natural Language Processing research and language analysis. We describe several Chinese language (Pǔtōnghuà) word embeddings, the differences from “western” language models caused by specific orthographic and linguistic features of the written Chinese language, and introduce a publicly available web interface for querying the vector models, aimed at linguistically or pedagogically oriented users.</p>
</abstract>

Vector models based on word embeddings are an indispensable part of advanced Natural Language Processing research and language analysis. We describe several Chinese language (Pǔtōnghuà) word embeddings, the differences from “western” language models caused by specific orthographic and linguistic features of the written Chinese language, and introduce a publicly available web interface for querying the vector models, aimed at linguistically or pedagogically oriented users.

Chinese Language Word Embeddings Based on the Corpus Hanku

Journal of Linguistics/Jazykovedný casopis

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Chinese Language Word Embeddings Based on the Corpus Hanku"}

Vector models based on word embeddings are an indispensable part of advanced Natural Language Processing research and language analysis. We describe several...

Chinese Language Word Embeddings Based on the Corpus Hanku

Publicado en línea: 17 ago 2022

Páginas: 996 - 1004

DOI: https://doi.org/10.2478/jazcas-2022-0023

Palabras clave
word embeddings, Chinese, Pǔtōnghuà, corpus, NLP

© 2022 Radovan Garabík, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Chinese Language Word Embeddings Based on the Corpus Hanku

Publicado en línea: 17 ago 2022

Páginas: 996 - 1004

DOI: https://doi.org/10.2478/jazcas-2022-0023

Palabras claveword embeddings, Chinese, Pǔtōnghuà, corpus, NLP

© 2022 Radovan Garabík, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
word embeddings, Chinese, Pǔtōnghuà, corpus, NLP