Novel Graph Topology Learning for Spatio-Temporal Analysis of COVID-19 Spread
Author:
Affiliation:
1. Global Big Data Technologies Center, University of Technology Sydney, Ultimo, NSW, Australia
2. Data61, CSIRO, Marsfield, NSW, Australia
3. Department of Communication Science and Engineering, Fudan University, Shanghai, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/10144459/10106414.pdf?arnumber=10106414
Reference45 articles.
1. Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic
2. Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding
3. Discovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States
4. A faster algorithm for betweenness centrality*
5. Analyzing Cross-country Pandemic Connectedness During COVID-19 Using a Spatial-Temporal Database: Network Analysis
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