Automatic Keyphrase Extraction from Scientific Chinese Medical Abstracts Based on Character-Level Sequence Labeling

Ding Liangping; Zhang Zhixiong; Liu Huan; Li Jie; Yu Gaihong

doi:10.2478/jdis-2021-0013

Journal of Data and Information Science (Mar 2021)

Automatic Keyphrase Extraction from Scientific Chinese Medical Abstracts Based on Character-Level Sequence Labeling

Ding Liangping,
Zhang Zhixiong,
Liu Huan,
Li Jie,
Yu Gaihong

Affiliations

Ding Liangping: National Science Library, Chinese Academy of Sciences, Beijing100190, China
Zhang Zhixiong: National Science Library, Chinese Academy of Sciences, Beijing100190, China
Liu Huan: National Science Library, Chinese Academy of Sciences, Beijing100190, China
Li Jie: National Science Library, Chinese Academy of Sciences, Beijing100190, China
Yu Gaihong: National Science Library, Chinese Academy of Sciences, Beijing100190, China

DOI: https://doi.org/10.2478/jdis-2021-0013
Journal volume & issue: Vol. 6, no. 3
pp. 35 – 57

Abstract

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Automatic keyphrase extraction (AKE) is an important task for grasping the main points of the text. In this paper, we aim to combine the benefits of sequence labeling formulation and pretrained language model to propose an automatic keyphrase extraction model for Chinese scientific research.

Published in Journal of Data and Information Science

ISSN: 2096-157X (Print); 2543-683X (Online)
Publisher: Sciendo
Country of publisher: Poland
LCC subjects: Technology: Technology (General): Industrial engineering. Management engineering: Information technology; Science: Mathematics: Instruments and machines: Electronic computers. Computer science
Website: https://sciendo.com/journal/JDIS

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