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Conference object . 2024
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https://dx.doi.org/10.48350/19...
Other literature type . 2024
Data sources: Datacite
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Article . 2024
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not opaque flow – Workflows zur Aufbereitung und Auswertung historischer Dokumente

Authors: Weber, Dominic; Schwandt, Silke; Huang, Angela; Hodel, Tobias; Tolino, Serena; Kuhlmann, Christopher; Meyer, Dana; +7 Authors

not opaque flow – Workflows zur Aufbereitung und Auswertung historischer Dokumente

Abstract

Deep Learning hat bereits neue Erkenntnisse in den digitalen Geisteswissenschaften ermöglicht. Vormoderne Sprachen und Sprachen des globalen Südens bringen allerdings Herausforderungen mit sich, die aktuell diesen analytischen Zugriff in diesem Bereich noch nicht erlauben. Das Projekt "The Flow" entwickelt Lösungen für solche historische Korpora in den Bereichen Handschriftenerkennung, Entitätsidentifikation, Event-Extraktion, Topic Modeling und Clustering. Die Entwicklung der Webanwendung nopaque zielt darauf ab, diese bestehenden Methoden bzw. Werkzeuge in einem übergreifenden Workflow zu verbinden. Der Workshop stellt den aktuellen Stand von nopaque bzw. den Workflow vor. Ziel ist es, bei der Etablierung eines allgemein anwendbaren Workflows für Deep Learning die Vielfalt der Quellen und geisteswissenschaftlichen Forschung zu berücksichtigen. Wir laden Teilnehmer:innen ein, Ideen und Erfahrungen einzubringen und Implementierungen für nicht standardisierte Layouts, Schriften und Sprachen zu diskutieren. Der Workshop trägt dazu bei, unser Projektziel zu erreichen: maschinelles Lernen in allen Bereichen der Geschichtswissenschaft zugänglicher zu machen.

Keywords

Paper, Machine Learning, Projektmanagement, Forschungsprozess, virtuelle Forschungsumgebungen, Werkzeuge, DHd2024, Modellierung, Workshop, Kollaboration, Workflows, Natural Language Processing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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