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Conference paper (unpublished)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... -
Research report
Data Study Group Final Report: Smart monitoring for conservation areas
WWF (World Wide Fund for Nature) monitors over 250,000 protected areas (e.g. national parks and nature reserves) and thousands of other sites and critical habitats. These sites are the foundation of global natural assets and are central to the preservation of biodiversity and human well-being. Unfortunately, they face increasing pressures... -
Abstract
Using smart annotations to map the geography of newspapers
Geographic information is a key component in the description of collection objects, and yet its format is often unsuited for use with methods of geographic analysis. Catalogue entries are often inconsistent, in plain text, and without geographic coordinates (much less coordinates linked to authority records). Georesolution of the relevant fields...Ryan, Yann ; Coll Ardanuy, Mariona ; van Strien, Daniel ; Hosseini, Kasra ; Beelen, Kaspar …
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Conference paper (unpublished)
Contextualizing Victorian Newspapers
Beelen, Kaspar ; Ahnert, Ruth ; Beavan, David ; Coll Ardanuy, Mariona ; Hosseini, Kasra …
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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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Dataset
Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
We present a new dataset for the task of toponym resolution in digitised 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...Coll Ardanuy, Mariona ; Beavan, David ; Beelen, Kaspar ; Hosseini, Kasra ; Lawrence, Jon …
nineteenth-century English, geographic information retrieval, newspapers, toponym resolution, and dataset
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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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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...