Realtime Disaster Detection Through GNN Models Using Disaster Knowledge Graphs-Reference-Cited by-同舟云学术

Realtime Disaster Detection Through GNN Models Using Disaster Knowledge Graphs

Published:2023-11-06 Issue: Volume:14 Page:221-228
ISSN:
Container-title:Proceedings of the International Conference on Advances in Social Networks Analysis and Mining
language:
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Author:

Kim Seonhyeong¹^ORCID,Khan Irshad²^ORCID,Kwon Young-Woo¹^ORCID

Affiliation:

1. Kyungpook National University, Daegu, South Korea

2. Kyungpook National University, Daegu, Republic of Korea

Funder

National Research Foundation of Korea

MSIT and Daegu Metropolitan City

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3625007.3627514

Reference21 articles.

1. Trend analysis of global disaster education research based on scientific knowledge graphs;Zhang M.;Sustainability,2022

2. Big data and disaster management: a systematic review and agenda for future research

3. Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management

4. Go social for your own safety! review of social networks use on natural disasters-case studies from worldwide;Dragović N.;Open Geosciences,2019

5. J. Kim and M. Hastak, "Social network analysis: Characteristics of online social networks after a disaster," International journal of information management, vol. 38, no. 1, pp. 86--96, 2018.

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