Results 21 to 30 of about 179 (112)

Geoparsing the Historical Gazetteers of Scotland: Accurately Computing Location in Mass Digitised Texts [PDF]

open access: yes, 2020
This paper describes work in progress on devising automatic and parallel methods for geoparsing large digital historical textual data by combining the strengths of three natural language processing (NLP) tools, the Edinburgh Geoparser, spaCy and defoe ...
Filgueira, Rosa   +5 more
core   +5 more sources

Multi-lingual geoparsing based on machine translation [PDF]

open access: yesFuture Generation Computer Systems, 2019
Abstract Our method for multi-lingual geoparsing uses monolingual tools and resources along with machine translation and alignment to return location words in many languages. Not only does our method save the time and cost of developing geoparsers for each language separately, but also it allows the possibility of a wide range of having a wide range ...
Xu Chen 0017   +3 more
openaire   +1 more source

A pragmatic guide to geoparsing evaluation

open access: yesLang. Resour. Evaluation, 2018
Accepted at Language Resources and Evaluation (Springer Journal)
Milan Gritta   +2 more
openaire   +5 more sources

Text‐analysis reveals taxonomic and geographic disparities in animal pollination literature

open access: yesEcography, Volume 43, Issue 1, Page 44-59, January 2020., 2020
Ecological systematic reviews and meta‐analyses have significantly increased our understanding of global biodiversity decline. However, for some ecological groups, incomplete and biased datasets have hindered our ability to construct robust, predictive models. One such group consists of the animal pollinators.
Joseph W. Millard   +2 more
wiley   +1 more source

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text [PDF]

open access: yesRemote Sensing, 2020
The automatic extraction of geospatial information is an important aspect of data mining. Computer systems capable of discovering geographic information from natural language involve a complex process called geoparsing, which includes two important tasks: geographic entity recognition and toponym resolution. The first task could be approached through a
Edwin Aldana-Bobadilla   +5 more
openaire   +2 more sources

Investigating News Deserts on the Content Level: Geographical Diversity in Swiss News Media [PDF]

open access: yes, 2023
With its diverse landscape of regional and local news media, Switzerland seems far from being a news desert. However, the centralization of editorial offices following the economic crisis of journalism has led to news outlets that share most of their ...
Weston, Morley   +2 more
core   +3 more sources

Multi-lingual Geoparsing based on Machine Translation

open access: yesCoRR, 2015
7 pages, 4 figures,
Xu Chen 0017   +2 more
openaire   +3 more sources

Automated Geoparsing of Paris Street Names in 19th Century Novels [PDF]

open access: yesProceedings of the 1st ACM SIGSPATIAL Workshop on Geospatial Humanities, 2017
Our project involves building a platform able to retrieve, map and analyze the occurrences of place names in fictional novels published between 1800 and 1914 and whose action occurs wholly or partly in Paris. We describe a proof of concept using queries made via the TXM textual analysis platform for the extraction of street names.
Ludovic Moncla   +3 more
openaire   +1 more source

Spatio-Temporal Information Extraction and Geoparsing for Public Chinese Resumes

open access: yesISPRS International Journal of Geo-Information, 2023
As an important carrier of individual information, the resume is an important data source for studying the spatio-temporal evolutionary characteristics of individual and group behaviors. This study focuses on spatio-temporal information extraction and geoparsing from resumes to provide basic technical support for spatio-temporal research based on ...
Xiaolong Li   +4 more
openaire   +2 more sources

Detecting and Modeling Emotional Landscapes Through Deep Learning, GPT‐4.1, and 3D Spatial Interpolation

open access: yesTransactions in GIS, Volume 30, Issue 1, February 2026.
ABSTRACT This research provides new directions in conceptualizing emotional geographies at the landscape level using a combination of textual deep learning (DL) and GPT‐based spatial emotion detection and interpolation using 3D empirical Bayesian kriging.
Christopher J. Anderson
wiley   +1 more source

Home - About - Disclaimer - Privacy