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Extending defoe for the efficient analysis of historical texts at scale
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dc.contributor.author | Filgueira, Rosa | |
dc.contributor.author | Grover, Claire | |
dc.contributor.author | Karaiskos, Vasilios | |
dc.contributor.author | Alex, Beatrice | |
dc.contributor.author | Van Eyndhoven, Sarah | |
dc.contributor.author | Gotthard, Lisa | |
dc.contributor.author | Terras, Melissa | |
dc.date.accessioned | 2022-02-10T16:30:01Z | |
dc.date.available | 2022-02-10T16:30:01Z | |
dc.date.issued | 2021-10-26 | |
dc.identifier | 277807290 | |
dc.identifier | a1d49da2-a02e-41db-9371-d2685eb0426e | |
dc.identifier | 85119072602 | |
dc.identifier.citation | Filgueira , R , Grover , C , Karaiskos , V , Alex , B , Van Eyndhoven , S , Gotthard , L & Terras , M 2021 , Extending defoe for the efficient analysis of historical texts at scale . in 17th IEEE International Conference on eScience 2021 . IEEE International Conference on eScience , IEEE , United States , pp. 21-29 , 17th IEEE International Conference on eScience 2021 , Innsbruck , Austria , 20/09/21 . https://doi.org/10.1109/eScience51609.2021.00012 | en |
dc.identifier.citation | conference | en |
dc.identifier.isbn | 9781665447089 | |
dc.identifier.isbn | 9781665403610 | |
dc.identifier.issn | 2325-3703 | |
dc.identifier.other | Bibtex: b658ffe64e1b4ae5b2cf684014476d20 | |
dc.identifier.uri | https://hdl.handle.net/10023/24848 | |
dc.description | Funding: This work was partly funded by the Data-Driven Innovation Programme as part of the Edinburgh and South East Scotland City Region Deal, by the University of Edinburgh, and by Google Cloud Platform research credits program. | en |
dc.description.abstract | This paper presents the new facilities provided in defoe, a parallel toolbox for querying a wealth of digitised newspapers and books at scale. defoe has been extended to work with further Natural Language Processing () tools such as the Edinburgh Geoparser, to store the preprocessed text in several storage facilities and to support different types of queries and analyses. We have also extended the collection of XML schemas supported by defoe, increasing the versatility of the tool for the analysis of digital historical textual data at scale. Finally, we have conducted several studies in which we worked with humanities and social science researchers who posed complex and interested questions to large-scale digital collections. Results shows that defoe allows researchers to conduct their studies and obtain results faster, while all the large-scale text mining complexity is automatically handled by defoe. | |
dc.format.extent | 9 | |
dc.format.extent | 8042178 | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.relation.ispartof | 17th IEEE International Conference on eScience 2021 | en |
dc.relation.ispartofseries | IEEE International Conference on eScience | en |
dc.subject | Digital tools | en |
dc.subject | Digitised primary historical sources | en |
dc.subject | Distributed queries | en |
dc.subject | High-Performance Computing | en |
dc.subject | Humanities research | en |
dc.subject | Text mining | en |
dc.subject | XML schemas | en |
dc.subject | C Auxiliary sciences of history (General) | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | NS | en |
dc.subject.lcc | C1 | en |
dc.subject.lcc | QA75 | en |
dc.title | Extending defoe for the efficient analysis of historical texts at scale | en |
dc.type | Conference item | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | 10.1109/eScience51609.2021.00012 | |
dc.identifier.url | https://www.research.ed.ac.uk/en/publications/extending-defoe-for-the-efficient-analysis-of-historical-texts-at | en |
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