Typicality of Lexical Bundles in Different Sections of Scientific Articles

Haotong Wang, Yves Lepage, Chooi Ling Goh

研究成果

抄録

This paper proposes a method to quantify the typicality of lexical bundles in sections of academic articles, specifically in the field of Natural Language Processing papers. Typicality is defined as the product of individual KL-divergence scores and the probability of a bundle to appear in a type of section. An evaluation of our typicality measure against two other baselines shows slight improvements according to the Silhouette coefficient.

本文言語English
ホスト出版物のタイトルSSPS 2020 - 2020 2nd Symposium on Signal Processing Systems
出版社Association for Computing Machinery
ページ56-60
ページ数5
ISBN(電子版)9781450388627
DOI
出版ステータスPublished - 2020 7 11
イベント2nd Symposium on Signal Processing Systems, SSPS 2020 - Virtual, Online, China
継続期間: 2020 7 112020 7 13

出版物シリーズ

名前PervasiveHealth: Pervasive Computing Technologies for Healthcare
ISSN(印刷版)2153-1633

Conference

Conference2nd Symposium on Signal Processing Systems, SSPS 2020
国/地域China
CityVirtual, Online
Period20/7/1120/7/13

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 情報システム
  • コンピュータ サイエンスの応用
  • 健康情報学

引用スタイル