Identifying multidisciplinary problems from scientific publications based on a text generation method

Affiliations

Xu Ziyan: Institute of Scientific and Technical Information of China, Beijing100038, China
Han Hongqi: Institute of Scientific and Technical Information of China, Beijing100038, China
Li Linna: Institute of Scientific and Technical Information of China, Beijing100038, China
Zhang Junsheng: Institute of Scientific and Technical Information of China, Beijing100038, China
Zhou Zexu: Institute of Scientific and Technical Information of China, Beijing100038, China

Abstract

A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation.

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