Identification and Prediction of Interdisciplinary Research Topics: A Study Based on the Concept Lattice Theory

Xu Haiyun; Wang Chao; Dong Kun; Yue Zenghui

doi:10.2478/jdis-2019-0004

Journal of Data and Information Science (Feb 2019)

Identification and Prediction of Interdisciplinary Research Topics: A Study Based on the Concept Lattice Theory

Xu Haiyun,
Wang Chao,
Dong Kun,
Yue Zenghui

Affiliations

Xu Haiyun: Institute of Scientific and Technical Information of China, Beijing 100038, Beijing, China
Wang Chao: Information research institute of Shandong Academy of sciences, Jinan 250014, Jinan, China
Dong Kun: Science and Technology Information Research Institute, Shandong University of Technology, Zibo 255091, Zibo, China
Yue Zenghui: School of Medical Information Engineering, Jining Medical University, Rizhao 276826, Zibo, China

DOI: https://doi.org/10.2478/jdis-2019-0004
Journal volume & issue: Vol. 4, no. 1
pp. 60 – 88

Abstract

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Formal concept analysis (FCA) and concept lattice theory (CLT) are introduced for constructing a network of IDR topics and for evaluating their effectiveness for knowledge structure exploration.

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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