An Assessment of Substitute Words in the Context of Academic Writing Proposed by Pre-trained and Specific Word Embedding Models

Chooi Ling Goh, Yves Lepage

研究成果: Conference contribution

抄録

Researchers who are non-native speakers of English always face some problems when composing scientific articles in this language. Most of the time, it is due to lack of vocabulary or knowledge of alternate ways of expression. In this paper, we suggest to use word embeddings to look for substitute words used for academic writing in a specific domain. Word embeddings may not only contain semantically similar words but also other words with similar word vectors, that could be better expressions. A word embedding model trained on a collection of academic articles in a specific domain might suggest similar expressions that comply to that writing style and are suited to that domain. Our experiment results show that a word embedding model trained on the NLP domain is able to propose possible substitutes that could be used to replace the target words in a certain context.

本文言語English
ホスト出版物のタイトルComputational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers
編集者Le-Minh Nguyen, Satoshi Tojo, Xuan-Hieu Phan, Kôiti Hasida
出版社Springer
ページ414-427
ページ数14
ISBN(印刷版)9789811561672
DOI
出版ステータスPublished - 2020
イベント16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019 - Hanoi, Viet Nam
継続期間: 2019 10 112019 10 13

出版物シリーズ

名前Communications in Computer and Information Science
1215 CCIS
ISSN(印刷版)1865-0929
ISSN(電子版)1865-0937

Conference

Conference16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019
CountryViet Nam
CityHanoi
Period19/10/1119/10/13

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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