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2019
Conference paper (published)
Resolving places, past and present: toponym resolution in historical British newspapers using multiple resources
Newspapers and their metadata are richly geographical, not only in their distribution but also their content. Attending to these spatial features is a prerequisite in newspaper research. Following other projects to have geoparsed place names in newspapers, we describe our approach to linking historical geospatial information in text to real-world...Coll Ardanuy, Mariona ; McDonough, Katherine ; Krause, Amrey ; Wilson, Daniel C.S. ; Hosseini, Kasra …
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2019
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2020
Conference paper (unpublished)
Assessing the Impact of OCR Quality on Downstream NLP Tasks
A growing volume of heritage data is being digitized and made available as text via optical character recognition (OCR). Scholars and libraries are increasingly using OCR-generated text for retrieval and analysis. However, the process of creating text through OCR introduces varying degrees of error to the text. The impact of... -
2020
Dataset
Living with Machines alpha and beta Zooniverse 'accident' task data
Data created through crowdsourcing tasks hosted on the Zooniverse platform. Members of the public were asked to look at a selection of articles from 19th century newspapers that mentioned machines and decide if they described an industrial accident. A further task asked participants to transcribe personal, organisational and place names...Zooniverse volunteers
crowdsourcing, digital history, citizen history, Living with Machines, newspapers, and digital humanities
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2020
Dataset
Living Machines atypical animacy dataset
Atypical animacy detection dataset, based on nineteenth-century sentences in English extracted from an open dataset of nineteenth-century books digitized by the British Library (available via https://doi.org/10.21250/db14, British Library Labs, 2014). This dataset contains 598 sentences containing mentions of machines. Each sentence has been annotated according to the animacy and humanness... -
2020
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
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