Node2vec Representation for Clustering Journals and as A Possible Measure of Diversity

Shen Zhesi; Chen Fuyou; Yang Liying; Wu Jinshan

doi:10.2478/jdis-2019-0010

Journal of Data and Information Science (Jun 2019)

Node2vec Representation for Clustering Journals and as A Possible Measure of Diversity

Shen Zhesi,
Chen Fuyou,
Yang Liying,
Wu Jinshan

Affiliations

Shen Zhesi: National Science Library, Chinese Academy of Sciences, Beijing100190, P.R.China
Chen Fuyou: National Science Library, Chinese Academy of Sciences, Beijing100190, P.R.China
Yang Liying: National Science Library, Chinese Academy of Sciences, Beijing100190, P.R.China
Wu Jinshan: School of Systems Science, Beijing Normal University, Beijing, 100875, P.R.China

DOI: https://doi.org/10.2478/jdis-2019-0010
Journal volume & issue: Vol. 4, no. 2
pp. 79 – 92

Abstract

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To investigate the effectiveness of using node2vec on journal citation networks to represent journals as vectors for tasks such as clustering, science mapping, and journal diversity measure.

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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Abstract

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