Organizational Geosocial Network: A Graph Machine Learning Approach Integrating Geographic and Public Policy Information for Studying the Development of Social Organizations in China.
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%0 Journal Article
%1 journals/ijgi/ZhaoWW22
%A Zhao, Xinjie
%A Wang, Shiyun
%A Wang, Hao
%D 2022
%J ISPRS Int. J. Geo Inf.
%K dblp
%N 5
%P 318
%T Organizational Geosocial Network: A Graph Machine Learning Approach Integrating Geographic and Public Policy Information for Studying the Development of Social Organizations in China.
%U http://dblp.uni-trier.de/db/journals/ijgi/ijgi11.html#ZhaoWW22
%V 11
@article{journals/ijgi/ZhaoWW22,
added-at = {2022-06-13T00:00:00.000+0200},
author = {Zhao, Xinjie and Wang, Shiyun and Wang, Hao},
biburl = {https://www.bibsonomy.org/bibtex/213d7ebf744b66fbd492a657cddef7470/dblp},
ee = {https://doi.org/10.3390/ijgi11050318},
interhash = {a8dfb3b85917e7a890cf757db69fcbb4},
intrahash = {13d7ebf744b66fbd492a657cddef7470},
journal = {ISPRS Int. J. Geo Inf.},
keywords = {dblp},
number = 5,
pages = 318,
timestamp = {2024-04-08T11:12:26.000+0200},
title = {Organizational Geosocial Network: A Graph Machine Learning Approach Integrating Geographic and Public Policy Information for Studying the Development of Social Organizations in China.},
url = {http://dblp.uni-trier.de/db/journals/ijgi/ijgi11.html#ZhaoWW22},
volume = 11,
year = 2022
}
