Use of Pretrained Language Models for Geographic Information Retrieval

<p>By using recent pre-trained language models in Geographic Information Retrieval (GIR), this study aims to find origins for place names in Melbourne (Australia). We propose a multi-objective ensemble model that balances the retrieval between semantic and spatial matching, with an emphasis on spatial recommendations.</p>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-20
DOI
https://doi.org/10.5281/zenodo.16908616
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Use of Pretrained Language Models for Geographic Information Retrieval

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Use of Pretrained Language Models for Geographic Information Retrieval

article en

Abstract

<p>By using recent pre-trained language models in Geographic Information Retrieval (GIR), this study aims to find origins for place names in Melbourne (Australia). We propose a multi-objective ensemble model that balances the retrieval between semantic and spatial matching, with an emphasis on spatial recommendations.</p>

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 66%
Geochemistry and Geologic Mapping
DOIOpen Access PDFOpenAlex
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Use of Pretrained Language Models for Geographic Information Retrieval · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS