Semantic Scholar

Semantic Scholar
Type of site
 Search engine
Created by Allen Institute for Artificial Intelligence
Website semanticscholar.org
Launched November 2015 (2015-11)

Semantic Scholar is a project developed at the Allen Institute for Artificial Intelligence, released in November 2015. It is designed to be a "smart" search service for journal articles.[1] The project uses a combination of machine learning, natural language processing, machine vision to add a layer of semantic analysis to the traditional methods of citation analysis.[2] In comparison to Google Scholar and PubMed, it is designed to quickly highlight the most important papers and identify the connections between them.

As of January 2018, following a 2017 project that added biomedical papers and topic summaries, the corpus now includes more than 40 million papers from computer science and biomedicine.[3] In March 2018, Doug Raymond, who developed machine learning initiatives for the Amazon Alexa platform was hired to lead the Semantic Scholar project.[4]

See also

References

  1. ↑ "Paul Allen's AI research group unveils program that aims to shake up how we search scientific knowledge. Give it a try". The Washington Post. Retrieved November 3, 2015.
  2. ↑ Bohannon, John (11 November 2016). "A computer program just ranked the most influential brain scientists of the modern era". sciencemag.org. American Association for the Advancement of Science. Retrieved 12 November 2016.
  3. ↑ "AI2 scales up Semantic Scholar search engine to encompass biomedical research". GeekWire. 2017-10-17. Retrieved 2018-01-18.
  4. ↑ "Tech Moves: Allen Instititue Hires Amazon Alexa Machine Learning Leader; Microsoft Chairman Takes on New Investor Role; and More". GeekWire.
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