Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages-Reference-Cited by-同舟云学术

Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

Published:2023-10-09 Issue:11 Volume:37 Page:2289-2318
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Hu Yingjie¹^ORCID,Mai Gengchen²^ORCID,Cundy Chris³,Choi Kristy³,Lao Ni⁴,Liu Wei¹,Lakhanpal Gaurish¹⁵,Zhou Ryan Zhenqi¹,Joseph Kenneth⁶

Affiliation:

1. GeoAI Lab, Department of Geography, University at Buffalo, Buffalo, NY, USA

2. Spatially Explicit Artificial Intelligence (SEAI) Lab, Department of Geography, University of Georgia, Athens, GA, USA

3. Department of Computer Science, Stanford University, Stanford, CA, USA

4. Google, Mountain View, CA, USA

5. Stevenson High School, Lincolnshire, IL, USA

6. Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY, USA

Funder

U.S. National Science Foundation

National Science Foundation

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2023.2266495

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5. A Novel Deep Learning Approach Using Contextual Embeddings for Toponym Resolution

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