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Conference paper (published)
MapReader: a computer vision pipeline for the semantic exploration of maps at scale
We present MapReader, a free, open-source software library written in Python for analyzing large map collections. MapReader allows users with little computer vision expertise to i) retrieve maps via web-servers; ii) preprocess and divide them into patches; iii) annotate patches; iv) train, fine-tune, and evaluate deep neural network models; and...Hosseini, Kasra ; Wilson, Daniel C. S. ; Beelen, Kaspar ; McDonough, Katherine
maps and ordnance survey
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Journal article
Neural Language Models for Nineteenth-Century English
We present four types of neural language models trained on a large historical dataset of books in English, published between 1760-1900 and comprised of ~5.1 billion tokens. The language model architectures include static (word2vec and fastText) and contextualized models (BERT and Flair). For each architecture, we trained a model instance...Hosseini, Kasra ; Beelen, Kaspar ; Colavizza, Giovanni ; Coll Ardanuy, Mariona
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Journal article
MapReader: A Computer Vision Pipeline for the Semantic Exploration of Maps at Scale
We present MapReader, a free, open-source software library written in Python for analyzing large map collections (scanned or born-digital). This library transforms the way historians can use maps by turning extensive, homogeneous map sets into searchable primary sources. MapReader allows users with little or no computer vision expertise to i)...Hosseini, Kasra ; Wilson, Daniel C.S. ; Beelen, Kaspar ; McDonough, Katherine
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Journal article
Maps of a Nation? The Digitized Ordnance Survey for New Historical Research
Although the Ordnance Survey has itself been the subject of historical research, scholars have not systematically used its maps as primary sources of information. This is partly for disciplinary reasons and partly for the technical reason that high-quality maps have not until recently been available digitally, geo-referenced, and in color....Hosseini, Kasra ; McDonough, Katherine ; van Strien, Daniel ; Vane, Olivia ; Wilson, Daniel C.S.
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Journal article
A Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
We present a new dataset for the task of toponym resolution in digitized historical newspapers in English. It consists of 343 annotated articles from newspapers based in four different locations in England (Manchester, Ashton-under-Lyne, Poole and Dorchester), published between 1780 and 1870. The articles have been manually annotated with mentions... -
Software
Living-with-machines/MapReader: End of LwM
This release marks the end of the current funding for MapReader during the Living with Machines (LwM) project. @kasra-hosseini @andrewphilipsmith @rwood-97 @kmcdono2 @dcsw2 @kallewesterling @kasparvonbeelenHosseini, Kasra ; Wood, Rosie ; Smith, Andy ; McDonough, Katie ; Wilson, Daniel C. S. …
computer vision and maps
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Dataset
Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
We present a new dataset (version 2) for the task of toponym resolution in digitised historical newspapers in English. It consists of 455 annotated articles from newspapers based in four different locations in England (Manchester, Ashton-under-Lyne, Poole and Dorchester), published between 1780 and 1870. The articles have been manually annotated...Coll Ardanuy, Mariona ; Beavan, David ; Beelen, Kaspar ; Hosseini, Kasra ; Lawrence, Jon …
nineteenth-century English, dataset, newspapers, toponym resolution, and geographic information retrieval
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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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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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