Identifying Variability in U.S. COVID-19 Response Through Temporal Partial Ordering Detection
Author:
Affiliation:
1. University of Alabama in Huntsville,Raytheon Technologies,Huntsville,AL,USA
2. Kennesaw State University,Department of Computer Science,Marietta,GA,USA
3. University of Alabama in Huntsville,Department of Computer Science,Huntsville,AL,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9994793/9994847/09995659.pdf?arnumber=9995659
Reference22 articles.
1. Cheat Detection Through Temporal Inference of Constrained Orders for Subsequences
2. The comparative politics of COVID-19: The need to understand government responses
3. Effectiveness of government policies in response to the first COVID-19 outbreak
4. In the eye of the storm … again ! Social policy responses to COVID‐19 in Southern Europe
5. Variation in us states’ responses to covid-19;Hallas;University of Oxford,2021
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1. Temporal information retrieval using bitwise operators;Information Retrieval Journal;2023-09-23
2. Confidence-Based Cheat Detection Through Constrained Order Inference of Temporal Sequences;International Journal of Semantic Computing;2023-04-10
3. Detection of Semantic Duplicates in Temporal Domains Using Directed Acyclic Graphs;SoutheastCon 2023;2023-04-01
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