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Dataset
DeezyMatch training set for OCR
Optical character recognition (OCR) is the process of automatically transcribing text from images. The presence of OCR-induced errors in digitised text is a common problem in the digital humanities. OCR errors are usually due to the misrecognition of characters, such as "h" recognised as "b", or "c" recognised as "o".... -
Living with Machines
User Collection -
Book
Collaborative Historical Research in the Age of Big Data
Living with Machines is the largest digital humanities project ever funded in the UK. The project brought together a team of twenty-three researchers to leverage more than twenty-years' worth of digitisation projects in order to deepen our understanding of the impact of mechanisation on nineteenth-century Britain. In contrast to many...Ahnert, Ruth ; Griffin, Emma ; Ridge, Mia ; Tolfo, Giorgia
digital humanities, British history, multidisciplinarity, digital history, and nineteenth century
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Conference paper (published)
Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0
In this work, we explore whether the recently demonstrated zero-shot abilities of the T0 model extend to Named Entity Recognition for out-of-distribution languages and time periods. Using a historical newspaper corpus in 3 languages as test-bed, we use prompts to extract possible named entities. Our results show that a naive...De Toni, Francesco ; Akiki, Christopher ; De La Rosa, Javier ; Fourrier, Clémentine ; Manjavacas, Enrique …
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Journal article
Under the Impression: Multispectral Imaging of Lord Frederick Campbell Charter XXI 5
Lord Frederick Campbell Charter 5 is the only surviving English document that still has an authentic, legible, pre-Conquest seal attached to it. The text purports to be a writ of Edward the Confessor (1003x5–1066) granting a slew of rights to Christ Church Cathedral, Canterbury. We examined the writ using multispectral...Hudson, Alison ; Duffy, Christina
multispectral imaging, digital humanities, conservation, seals, early medieval history, writs, and Norman Conquest
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Abstract
Historic machines from 'prams' to 'Parliament': new avenues for collaborative linguistic research
Research in computational linguistics has made successful attempts at modelling word meaning at scale, but much remains to be done to put these computational models to the test of historical scholarship (see e.g. Beelen et al. 2021). More importantly, a lot of computational research looks at texts in a historical...Ridge, Mia ; Tolfo, Giorgia ; Westerling, Kalle ; Pedrazzini, Nilo ; McGillivray, Barbara
crowdsourcing, computational linguistics, and digital humanities
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Conference paper (unpublished)
A Deep Learning Approach to Geographical Candidate Selection through Toponym Matching
Recognizing toponyms and resolving them to their real-world referents is required for providing advanced semantic access to textual data. This process is often hindered by the high degree of variation in toponyms. Candidate selection is the task of identifying the potential entities that can be referred to by a toponym... -
Dataset
StopsGB: Structured Timeline of Passenger Stations in Great Britain
Michael Quick's book _Railway Passenger Stations in Great Britain: a Chronology_ offers a uniquely rich and detailed account of Britain's changing railway infrastructure. Its listing of over 12,000 stations allows us to reconstruct the coming of rail at both micro- and macro-scales. However, being published originally as a book (and... -
Journal article
Can I believe what I see? Data visualisation and trust in the humanities
Questions of trust are increasingly important in relation to data and its use. The authors focus on humanities data and its visualisation, through analysis of their own recent projects with museums, archives and libraries internationally. Their account connects the specifics of hands-on digital humanities work to larger epistemological questions. They...Boyd Davis, Stephen ; Vane, Olivia ; Kräutli, Florian
scepticism, critical design, interdisciplinarity, ethics, digital humanities, interrogability, data visualisation, and GLAM
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Conference paper (published)
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching
We present DeezyMatch, a free, open-source software library written in Python for fuzzy string matching and candidate ranking. Its pair classifier supports various deep neural network architectures for training new classifiers and for fine-tuning a pretrained model, which paves the way for transfer learning in fuzzy string matching. This approach...Hosseini, Kasra ; Nanni, Federico ; Coll Ardanuy, Mariona
Natural Language Processing, string matching, toponym matching, machine learning, and digital humanities