Semantic Scholar

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Semantic Scholar
Semantic Scholar logo.png
Type of site
Search engine
Created byAllen Institute for Artificial Intelligence
URLsemanticscholar.org
LaunchedNovember 2015 (2015-11)

Semantic Scholar is an artificial-intelligence backed search engine for academic publications that was developed at the Allen Institute for Artificial Intelligence and publicly released in November 2015.[1] It uses recent advances in natural language processing to provide summaries for scholarly papers.[2]

Technology[edit]

Semantic Scholar provides one-sentence summary of scientific literature. One of its aims was to address the challenge of reading numerous titles and lengthy abstracts on mobile devices.[3] It also seeks to ensure that the three million scientific papers published yearly reach readers since it is estimated that only half of this literature are ever read.[4]

Artificial intelligence is used to capture the essence of a paper, generating it through an "abstractive" technique.[2] The project uses a combination of machine learning, natural language processing, and machine vision to add a layer of semantic analysis to the traditional methods of citation analysis, and to extract relevant figures, entities, and venues from papers.[5] In comparison to Google Scholar and PubMed, Semantic Scholar is designed to highlight the most important and influential papers, and to identify the connections between them. Each paper hosted by Semantic Scholar is assigned a unique identifier called the Semantic Scholar Corpus ID (or S2CID for short), for example

Liu, Ying; Gayle, Albert A; Wilder-Smith, Annelies; Rocklöv, Joacim (March 2020). "The reproductive number of COVID-19 is higher compared to SARS coronavirus". Journal of Travel Medicine. 27 (2). doi:10.1093/jtm/taaa021. PMC 7074654. PMID 32052846. S2CID 211099356.

As of January 2018, following a 2017 project that added biomedical papers and topic summaries, the Semantic Scholar corpus included more than 40 million papers from computer science and biomedicine.[6] In March 2018, Doug Raymond, who developed machine learning initiatives for the Amazon Alexa platform, was hired to lead the Semantic Scholar project.[7] As of August 2019, the number of included papers had grown to more than 173 million[8] after the addition of the Microsoft Academic Graph records.[9]

In 2020, users of Semantic Scholar reached seven million a month.[3]

See also[edit]

References[edit]

  1. ^ Ariana Eunjung Cha (3 November 2015). "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. Archived from the original on 6 November 2019. Retrieved November 3, 2015.
  2. ^ a b Hao, Karen (November 18, 2020). "An AI helps you summarize the latest in AI". MIT Technology Review. Retrieved 2021-02-16.
  3. ^ a b Grad, Peter (November 24, 2020). "AI tool summarizes lengthy papers in a sentence". techxplore.com. Retrieved 2021-02-16.
  4. ^ "Allen Institute's Semantic Scholar now searches across 175 million academic papers". VentureBeat. 2019-10-23. Retrieved 2021-02-16.
  5. ^ Bohannon, John (11 November 2016). "A computer program just ranked the most influential brain scientists of the modern era". Science. doi:10.1126/science.aal0371. Archived from the original on 29 April 2020. Retrieved 12 November 2016.
  6. ^ "AI2 scales up Semantic Scholar search engine to encompass biomedical research". GeekWire. 2017-10-17. Archived from the original on 2018-01-19. Retrieved 2018-01-18.
  7. ^ "Tech Moves: Allen Instititue Hires Amazon Alexa Machine Learning Leader; Microsoft Chairman Takes on New Investor Role; and More". GeekWire. 2018-05-02. Archived from the original on 2018-05-10. Retrieved 2018-05-09.
  8. ^ "main page". Semantic Scholar. Archived from the original on 11 August 2019. Retrieved 11 August 2019.
  9. ^ "AI2 joins forces with Microsoft Research to upgrade search tools for scientific studies". GeekWire. 2018-12-05. Archived from the original on 2019-08-25. Retrieved 2019-08-25.

External links[edit]

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