Abstract

By using of Ucinet software, this paper finds out several representative research teams in persionalized information service (PIS) field through establishing the 2-mode bipartite graph of key words and author, based on the 7426 research papers about PIS from 2008--2017 in Chinese academic literature web database. We also find out the team core characters and the subject research hotspots of the PIS fields according to the degree centrality index.This paper give out a new way for discovering the research teams using the 2-mode bipartite network.

Details

Title
Empricial Study of the Research Team Discovery Based on 2-Mode Bipartite Graph --Illustrated by the Case of the Research Teams Discovery in PIS Field
Author
JIAO, Hong; SHAO Zuoyun; ZHOU, Na
Pages
47-51
Section
Network technology
Publication year
2018
Publication date
2018
Publisher
Agricultural Information Institute of Chinese Academy of Agricultural Sciences
ISSN
10021248
Source type
Scholarly Journal
Language of publication
Chinese
DOI
https://doi.org/10.13998/j.cnki.issn1002-1248.2018.12.008
ProQuest document ID
2861358509
Copyright
© 2018. This work is published under https://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.