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dc.contributor.authorBainbridge, Daviden_NZ
dc.contributor.authorDownie, J. Stephenen_NZ
dc.contributor.authorCapitanu, Borisen_NZ
dc.coverage.spatialFort Worth, Texasen_NZ
dc.date.accessioned2018-07-11T02:33:24Z
dc.date.available2018en_NZ
dc.date.available2018-07-11T02:33:24Z
dc.date.issued2018en_NZ
dc.identifier.citationBainbridge, D., Downie, J. S., & Capitanu, B. (2018). Providing pin-point page-level precision to 1 trillion tokens of text for workset creation. In Proceedings of 18th ACM/IEEE Joint Conference on Digital Libraries (JCDL 2018) (pp. 407–408). New York, USA: ACM. https://doi.org/10.1145/3197026.3203875en
dc.identifier.isbn978-1-4503-5178-2en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/11929
dc.description.abstractWe report on the work undertaken developing a web environment that allows users to search over 1 trillion tokens of text -- down to the page-level -- of the HathiTrust Part-of-Speech Extracted Features Dataset to help produce worksets for scholarly analysis. We present an extended example of the web environment in use, along with details about its implementation.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherACMen_NZ
dc.rights© 2018 Copyright held by the author(s).
dc.sourceJCDL 2018en_NZ
dc.subjectcomputer scienceen_NZ
dc.subjectvery large digital librariesen_NZ
dc.subjectextract feature text analysisen_NZ
dc.subjectworkset creationen_NZ
dc.titleProviding pin-point page-level precision to 1 trillion tokens of text for workset creationen_NZ
dc.typeConference Contribution
dc.identifier.doi10.1145/3197026.3203875en_NZ
dc.relation.isPartOfProceedings of 18th ACM/IEEE Joint Conference on Digital Libraries (JCDL 2018)en_NZ
pubs.begin-page407
pubs.elements-id225045
pubs.end-page408
pubs.finish-date2018-06-07en_NZ
pubs.place-of-publicationNew York, USA
pubs.start-date2018-06-03en_NZ


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