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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao http://dx.doi.org/10...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/bigdat...
Article . 2013 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Customising geoparsing and georeferencing for historical texts

Authors: C. J. Rupp; Paul Rayson; Alistair Baron; Christopher Donaldson; Ian N. Gregory; Andrew Hardie; Patricia Murrieta-Flores;

Customising geoparsing and georeferencing for historical texts

Abstract

In order to better support the text mining of historical texts, we propose a combination of complementary techniques from Geographical Information Systems, computational and corpus linguistics. In previous work, we have described this as `visual gisting' to extract important themes from text and locate those themes on a map representing geographical information contained in the text. Here, we describe the steps that were found necessary to apply standard analysis and resolution tools to identify place names in a specific corpus of historical texts. This task is seen as an initial and prerequisite step for further analysis and comparison by combining the information we extract from a corpus with information from other sources, including other text corpora. The process is intended to support close reading of historical texts on a much larger scale by highlighting using exploratory and data-driven approaches which parts of the corpus warrant further close analysis. Our case study presented here is from a corpus of Lake District travel literature. We discuss the customisations that we have to make to existing tools to extract placename information and visualise it on a map.

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United Kingdom
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Average
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