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The Semantic Scholar Open Data Platform

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Kinney, Rodney, Anastasiades, Chloe, Authur, Russell, Beltagy, Iz, Bragg, Jonathan, Buraczynski, Alexandra, Cachola, Isabel, Candra, Stefan, Chandrasekhar, Yoganand, Cohan, Arman, Crawford, Miles, Downey, Doug, Dunkelberger, Jason, Etzioni, Oren, Evans, Rob, Feldman, Sergey, Gorney, Joseph, Graham, David, Hu, Fangzhou, Huff, Regan, King, Daniel, Kohlmeier, Sebastian, Kuehl, Bailey, Langan, Michael, Lin, Daniel, Liu, Haokun, Lo, Kyle, Lochner, Jaron, MacMillan, Kelsey, Murray, Tyler, Newell, Chris, Rao, Smita, Rohatgi, Shaurya, Sayre, Paul, Shen, Zejiang, Singh, Amanpreet, Soldaini, Luca, Subramanian, Shivashankar, Tanaka, Amber, Wade, Alex D., Wagner, Linda, Wang, Lucy Lu, Wilhelm, Chris, Wu, Caroline, Yang, Jiangjiang, Zamarron, Angele, Van Zuylen, Madeleine, Weld, Daniel S.
Format:	Preprint
Publié:	2023
Sujets:	Digital Libraries Computation and Language
Accès en ligne:	Acceder al recurso
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author	Kinney, Rodney Anastasiades, Chloe Authur, Russell Beltagy, Iz Bragg, Jonathan Buraczynski, Alexandra Cachola, Isabel Candra, Stefan Chandrasekhar, Yoganand Cohan, Arman Crawford, Miles Downey, Doug Dunkelberger, Jason Etzioni, Oren Evans, Rob Feldman, Sergey Gorney, Joseph Graham, David Hu, Fangzhou Huff, Regan King, Daniel Kohlmeier, Sebastian Kuehl, Bailey Langan, Michael Lin, Daniel Liu, Haokun Lo, Kyle Lochner, Jaron MacMillan, Kelsey Murray, Tyler Newell, Chris Rao, Smita Rohatgi, Shaurya Sayre, Paul Shen, Zejiang Singh, Amanpreet Soldaini, Luca Subramanian, Shivashankar Tanaka, Amber Wade, Alex D. Wagner, Linda Wang, Lucy Lu Wilhelm, Chris Wu, Caroline Yang, Jiangjiang Zamarron, Angele Van Zuylen, Madeleine Weld, Daniel S.
author_facet	Kinney, Rodney Anastasiades, Chloe Authur, Russell Beltagy, Iz Bragg, Jonathan Buraczynski, Alexandra Cachola, Isabel Candra, Stefan Chandrasekhar, Yoganand Cohan, Arman Crawford, Miles Downey, Doug Dunkelberger, Jason Etzioni, Oren Evans, Rob Feldman, Sergey Gorney, Joseph Graham, David Hu, Fangzhou Huff, Regan King, Daniel Kohlmeier, Sebastian Kuehl, Bailey Langan, Michael Lin, Daniel Liu, Haokun Lo, Kyle Lochner, Jaron MacMillan, Kelsey Murray, Tyler Newell, Chris Rao, Smita Rohatgi, Shaurya Sayre, Paul Shen, Zejiang Singh, Amanpreet Soldaini, Luca Subramanian, Shivashankar Tanaka, Amber Wade, Alex D. Wagner, Linda Wang, Lucy Lu Wilhelm, Chris Wu, Caroline Yang, Jiangjiang Zamarron, Angele Van Zuylen, Madeleine Weld, Daniel S.
contents	The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website aimed at accelerating science by helping scholars discover and understand scientific literature. We combine public and proprietary data sources using state-of-the-art techniques for scholarly PDF content extraction and automatic knowledge graph construction to build the Semantic Scholar Academic Graph, the largest open scientific literature graph to-date, with 200M+ papers, 80M+ authors, 550M+ paper-authorship edges, and 2.4B+ citation edges. The graph includes advanced semantic features such as structurally parsed text, natural language summaries, and vector embeddings. In this paper, we describe the components of the S2 data processing pipeline and the associated APIs offered by the platform. We will update this living document to reflect changes as we add new data offerings and improve existing services.
format	Preprint
id	arxiv_https___arxiv_org_abs_2301_10140
institution	arXiv
publishDate	2023
record_format	arxiv
spellingShingle	The Semantic Scholar Open Data Platform Kinney, Rodney Anastasiades, Chloe Authur, Russell Beltagy, Iz Bragg, Jonathan Buraczynski, Alexandra Cachola, Isabel Candra, Stefan Chandrasekhar, Yoganand Cohan, Arman Crawford, Miles Downey, Doug Dunkelberger, Jason Etzioni, Oren Evans, Rob Feldman, Sergey Gorney, Joseph Graham, David Hu, Fangzhou Huff, Regan King, Daniel Kohlmeier, Sebastian Kuehl, Bailey Langan, Michael Lin, Daniel Liu, Haokun Lo, Kyle Lochner, Jaron MacMillan, Kelsey Murray, Tyler Newell, Chris Rao, Smita Rohatgi, Shaurya Sayre, Paul Shen, Zejiang Singh, Amanpreet Soldaini, Luca Subramanian, Shivashankar Tanaka, Amber Wade, Alex D. Wagner, Linda Wang, Lucy Lu Wilhelm, Chris Wu, Caroline Yang, Jiangjiang Zamarron, Angele Van Zuylen, Madeleine Weld, Daniel S. Digital Libraries Computation and Language The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website aimed at accelerating science by helping scholars discover and understand scientific literature. We combine public and proprietary data sources using state-of-the-art techniques for scholarly PDF content extraction and automatic knowledge graph construction to build the Semantic Scholar Academic Graph, the largest open scientific literature graph to-date, with 200M+ papers, 80M+ authors, 550M+ paper-authorship edges, and 2.4B+ citation edges. The graph includes advanced semantic features such as structurally parsed text, natural language summaries, and vector embeddings. In this paper, we describe the components of the S2 data processing pipeline and the associated APIs offered by the platform. We will update this living document to reflect changes as we add new data offerings and improve existing services.
title	The Semantic Scholar Open Data Platform
topic	Digital Libraries Computation and Language
url	https://arxiv.org/abs/2301.10140