Geographic Named Entity Matching and Evaluation Recommendation Using Multi-Objective Tasks: A Study Integrating a Large Language Model (LLM) and Retrieval-Augmented Generation (RAG)

Geographic Named Entity Matching and Evaluation Recommendation Using Multi-Objective Tasks: A Study Integrating a Large Language Model (LLM) and Retrieval-Augmented Generation (RAG)

Geographical named entity matching, a crucial step in address encoding, aims to enhance address resolution accuracy through the precise identification and linkage of geographical named entity data. However, existing approaches tend to ignore the spatial information of entities, leading to misclassif...

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Bibliographic Details
Main Authors: Jiajun Zhang, Junjie Fang, Chengkun Zhang, Wei Zhang, Huanbing Ren, Liuchang Xu
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:ISPRS International Journal of Geo-Information
Subjects:
geographical named entity matching
multi-objective
Retrieval-Augmented Generation (RAG)
large language model (LLM)
geographical named entity recommendation
Online Access:https://www.mdpi.com/2220-9964/14/3/95
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