Automatic Terminology Extraction using A Dependency-Graph in NLP

Yusuke Kimura Kazuma Kusu Kenji Hatano Tokiya Baba
雑誌・プロシーディングス名: International Conference on Innovations in Bio-Inspired Computing and Applications
国名(英語): Online
言語: English
出版社: Springer, Cham
Vol.: 1372
ページ: 411-421
出版年: 2021
出版月: 4
出版日: 2021-04-10
DOI: 10.1007/978-3-030-73603-3_38
       

概要

Automatic Terminology Extraction (ATE) is a technique for extracting phrases representing a dataset. This technique is required for translating specialistic books and documents. An existing method focused on the fact that terminologies tend to be composed of two or more single nouns. However, it does not deal with modification relations but only co-occurrence relations among single nouns. Moreover, we have to consider the fact that phrases defined as terminology tend to be explained in another sentence when we propose a novel approach. In this study, we propose a method for extracting terminologies from a dataset considering the modification relations obtained by dependency analysis. In particular, we propose how to extract features enabling us to distinguish whether or not the phrase is terminology from a dependency structure of a sentence.

引用情報

Yusuke Kimura, Kazuma Kusu, Kenji Hatano, Tokiya Baba, Automatic Terminology Extraction using A Dependency-Graph in NLP, International Conference on Innovations in Bio-Inspired Computing and Applications, Vol.1372, pp.411-421, 2021-04-10, DOI: 10.1007/978-3-030-73603-3_38.

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