Difference between revisions of "Find More COVID-19 Papers"

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To discover more COVID-19 academic papers (to peer-review on OmniJournal), we highly recommend https://discovid.ai
 
To discover more COVID-19 academic papers (to peer-review on OmniJournal), we highly recommend https://discovid.ai
  
Discovid uses advanced machine learning to group papers by similarity to each other. After searching on Discovid, you can expand an article by clicking on it in the search results. When the article expands, similar papers will be displayed underneath its summary.
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Discovid uses advanced machine learning to group papers by similarity to each other. After searching on Discovid, you can expand an article by clicking on it in the search results. When the article expands, similar papers will be displayed underneath its summary. This is not your run-of-the-mill "related papers" feature. Instead, due to the advanced machine learning, it matches papers with similar topics extremely well and with considerable depth.
  
 
You can watch the introductory video for Discovid here: https://www.kaggle.com/danielwolffram/topic-modeling-finding-related-articles
 
You can watch the introductory video for Discovid here: https://www.kaggle.com/danielwolffram/topic-modeling-finding-related-articles
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Discovid uses the [https://www.semanticscholar.org/cord19 CORD-19 Dataset].
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You can also use the [https://cord-19.apps.allenai.org/ CORD-19 Explorer], as an alternative to Discovid, to search the [https://www.semanticscholar.org/cord19 CORD-19 Dataset].
  
 
If you come across additional COVID-19 academic indexes, please [[Contact_Us|email us]] so we can update this page. Thanks!
 
If you come across additional COVID-19 academic indexes, please [[Contact_Us|email us]] so we can update this page. Thanks!

Revision as of 06:24, 31 July 2020

To see all pages on OmniJournal, see all pages.

To discover more COVID-19 academic papers (to peer-review on OmniJournal), we highly recommend https://discovid.ai

Discovid uses advanced machine learning to group papers by similarity to each other. After searching on Discovid, you can expand an article by clicking on it in the search results. When the article expands, similar papers will be displayed underneath its summary. This is not your run-of-the-mill "related papers" feature. Instead, due to the advanced machine learning, it matches papers with similar topics extremely well and with considerable depth.

You can watch the introductory video for Discovid here: https://www.kaggle.com/danielwolffram/topic-modeling-finding-related-articles

Discovid uses the CORD-19 Dataset.

You can also use the CORD-19 Explorer, as an alternative to Discovid, to search the CORD-19 Dataset.

If you come across additional COVID-19 academic indexes, please email us so we can update this page. Thanks!