Towards Semantic Exploration of Tables in Scientific Documents

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dc.contributor.authorMulwad, Varish
dc.contributor.authorKumar, Vijay S.
dc.contributor.authorWilliams, Jenny Weisenberg
dc.contributor.authorFinin, Tim
dc.contributor.authorDixit, Sharad
dc.contributor.authorJoshi, Anupam
dc.date.accessioned2023-05-22T19:12:28Z
dc.date.available2023-05-22T19:12:28Z
dc.date.issued2023-05-28
dc.descriptionCEUR Workshop Proceedingsen_US
dc.description.abstractStructured data artifacts such as tables are widely used in scientific literature to organize and concisely communicate important statistical information. Discovering relevant information in these tables remains a significant challenge owing to their structural heterogeneity, dense and often implicit semantics, and diffuse context. This paper describes how we leverage semantic technologies to enable technical experts to search and explore tabular data embedded within scientific documents. We present a system for the on-demand construction of knowledge graphs representing scientific tables (drawn from online scholarly articles hosted by PubMed Central), and for synthesizing tabular responses to semantic search requests against such graphs. We discuss key differentiators in our overall approach, including a two-stage semantic table interpretation that relies on an extensive structural and syntactic characterization of scientific tables, and a prototype knowledge discovery engine that uses automatically-inferred semantics of scientific tables to serve search requests by potentially fusing information from multiple tables on the fly. We evaluate our system on a real-world dataset of approximately 120,000 tables extracted from over 62,000 COVID-19-related scientific articles.en_US
dc.description.sponsorshipThis research is based on work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via [2021-21022600004]. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U.S. Government.en_US
dc.description.urihttps://ceur-ws.org/Vol-3443/ESWC_2023_SemTech4STLD_paper_2.pdfen_US
dc.format.extent12 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2thu5-ar0a
dc.identifier.citationMulwad, Varish, et al. "Towards Semantic Exploration of Tables in Scientific Documents" Proceedings of the ESWC 2023 Workshops and Tutorials; 1 st International Workshop on SemTech4STLD, May 28, 2023, Hersonissos, Greece (28 May, 2023). https://ceur-ws.org/Vol-3443/ESWC_2023_SemTech4STLD_paper_2.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/28042
dc.language.isoen_USen_US
dc.publisherCEURen_US
dc.publisherCEUR-WS
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleTowards Semantic Exploration of Tables in Scientific Documentsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-6593-1792en_US
dcterms.creatorhttps://orcid.org/0000-0002-8641-3193en_US

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