Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Customising geoparsing and georeferencing for historical texts
AU - Rupp, C. J.
AU - Rayson, Paul
AU - Baron, Alistair
AU - Donaldson, Christopher
AU - Gregory, Ian
AU - Hardie, Andrew
AU - Murrieta-Flores, Patricia
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
U2 - 10.1109/BigData.2013.6691671
DO - 10.1109/BigData.2013.6691671
M3 - Conference contribution/Paper
SP - 59
EP - 62
BT - Proceedings of the 2013 IEEE International Conference on Big Data
PB - IEEE
ER -