Semantic Scholar

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Semantic Scholar
Allen Institute for Artificial Intelligence
URLsemanticscholar.org
LaunchedNovember 2015 (2015-11)

Semantic Scholar is an artificial intelligence–powered research tool for scientific literature developed at the Allen Institute for AI and publicly released in November 2015.[1] It uses advances in natural language processing to provide summaries for scholarly papers.[2] The Semantic Scholar team is actively researching the use of artificial-intelligence in natural language processing, machine learning, Human-Computer interaction, and information retrieval.[3]

Semantic Scholar began as a database surrounding the topics of

biomedical literature in its corpus.[4] As of September 2022, they now include over 200 million publications from all fields of science.[5]

Technology

Semantic Scholar provides a 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.[6] 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.[7]

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, tables, entities, and venues from papers.[8][9]

In contrast with Google Scholar and PubMed, Semantic Scholar is designed to highlight the most important and influential elements of a paper.[10] The AI technology is designed to identify hidden connections and links between research topics.[11] Like the previously cited search engines, Semantic Scholar also exploits graph structures, which include the Microsoft Academic Knowledge Graph, Springer Nature's SciGraph, and the Semantic Scholar Corpus.[12]

Each paper hosted by Semantic Scholar is assigned a unique identifier called the Semantic Scholar Corpus ID (abbreviated S2CID). The following entry is an 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).
S2CID 211099356
.

Semantic Scholar is free to use and unlike similar search engines (i.e. Google Scholar) does not search for material that is behind a paywall.[13][4]

One study compared the search abilities of Semantic Scholar through a systematic approach, and found the search engine to be 98.88% accurate when attempting to uncover the data.[13] The same study examined other Semantic Scholar functions, including tools to survey metadata as well as several citation tools.[13]

Number of users and publications

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

Microsoft Academic Graph records.[17] In 2020, a partnership between Semantic Scholar and the University of Chicago Press Journals made all articles published under the University of Chicago Press available in the Semantic Scholar corpus.[18] At the end of 2020, Semantic Scholar had indexed 190 million papers.[19]

In 2020, users of Semantic Scholar reached seven million a month.[6]

See also

References

  1. ^ Eunjung Cha, Ariana (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. ^ "Semantic Scholar Research". research.semanticscholar.org. Retrieved 2021-11-22.
  4. ^
    S2CID 45802944
    .
  5. ^ Matthews, David (1 September 2021). "Drowning in the literature? These smart software tools can help". Nature. Retrieved 5 September 2022. ...the publicly available corpus compiled by Semantic Scholar — a tool set up in 2015 by the Allen Institute for Artificial Intelligence in Seattle, Washington — amounting to around 200 million articles, including preprints.
  6. ^ a b Grad, Peter (November 24, 2020). "AI tool summarizes lengthy papers in a sentence". Tech Xplore. Retrieved 2021-02-16.
  7. ^ "Allen Institute's Semantic Scholar now searches across 175 million academic papers". VentureBeat. 2019-10-23. Retrieved 2021-02-16.
  8. from the original on 29 April 2020. Retrieved 12 November 2016.
  9. .
  10. ^ "Semantic Scholar". International Journal of Language and Literary Studies. Retrieved 2021-11-09.
  11. .
  12. .
  13. ^ .
  14. ^ "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.
  15. ^ "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.
  16. ^ "Semantic Scholar". Semantic Scholar. Archived from the original on 11 August 2019. Retrieved 11 August 2019.
  17. ^ "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.
  18. ^ "The University of Chicago Press joins more than 500 publishers working with Semantic Scholar to improve search and discoverability". RCNi Company Limited. Retrieved 2021-11-22.
  19. ^ Dunn, Adriana (December 14, 2020). "Semantic Scholar Adds 25 Million Scientific Papers in 2020 Through New Publisher Partnerships" (PDF). Semantic Scholar. Retrieved November 22, 2021.

External links