Fast Mining and Forecasting of Co-evolving Epidemiological Data Streams-Reference-Cited by-同舟云学术

Fast Mining and Forecasting of Co-evolving Epidemiological Data Streams

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Kimura Tasuku¹,Matsubara Yasuko¹,Kawabata Koki¹,Sakurai Yasushi¹

Affiliation:

1. Osaka University, Osaka, Japan

Funder

Japan Society for the Promotion of Science

JST-AIP

MIC/SCOPE

JST-Mirai Program

National Institute of Information and Communications Technology

Publisher

ACM

Link

Reference56 articles.

1. https://www.who.int/emergencies/diseases/novel-coronavirus-2019. https://www.who.int/emergencies/diseases/novel-coronavirus-2019.

2. https://protect-public.hhs.gov/. https://protect-public.hhs.gov/.

3. https://www.rki.de/EN/Home/homepage_node.html. https://www.rki.de/EN/Home/homepage_node.html.

4. EpiCast. https://sites.google.com/view/epicast-demo/home. EpiCast. https://sites.google.com/view/epicast-demo/home.

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