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2022
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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2020
Conference paper (unpublished)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... -
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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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Conference paper (unpublished)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...