Unlocking the Schematismus: A Machine Learning and Data-driven Approach Toward Mapping Habsburg Middle Class in the Long 19th Century
Unlocking the Schematismus: A Machine Learning and Data-driven Approach Toward Mapping Habsburg Middle Class in the Long 19th Century
Wolfgang Göderle
(ORCID: 0000-0002-9417-5316)
Disciplines
Other Humanities (34%); History, Archaeology (33%); Computer Sciences (33%)
Keywords
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Modern History,
Information Extraction,
Machine Learning,
Historical Research Database,
Network Analysis,
Historical Prosopography
Consortium
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consortium member
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consortium member
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consortium member
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coordinator
Research institution(s)
- Universität Graz
International project participants
- Martin Klecacky, Academy of Sciences of the Czech Republic - Czechia
- František Darena, Mendel University Brno - Czechia
- Christine Lebeau, Université Paris 1 - Panthéon Sorbonne - France
- Jana Osterkamp, Universität Augsburg - Germany
- Viktor Karády, Central European University Private University - Hungary
- Gabor Egry, Institute of Political History - Hungary
- Giancarlo Ruffo, Università degli Studi del Piemonte Orientale - Italy
- Vlad Popovici, Czech Academy of Sciences - Romania
- Dasa Licen, Karst Research Institute ZRC SAZU - Slovenia
- Martin Grandjean, University of Lausanne - Switzerland
- John Deak, University of Notre Dame - USA
- Deborah Coen, Yale University - USA