Construction and Inference Method of Semantic-Driven, Spatio-Temporal Derivation Relationship Network for Place Names

As the proper noun for geographical entities, place names provide an intuitive way to identify and access specific geographic locations, playing a key role in semantic expression and spatial retrieval. However, existing research has insufficiently explored the spatio-temporal derivation relationships of place names, failing to fully utilize these relationships to enhance the connectivity between place names and improve spatial retrieval capabilities. Therefore, this paper conducts research on the spatio-temporal derivation relationships of place names, defines them in a standardized manner, clarifies the boundary conditions and identification methods, and then constructs a spatio-temporal derivation network of place names for expression and uses this network to carry out reasoning research on spatial adjacency relationships. Experiments and results showed that using the theory and methods of this paper to identify the spatio-temporal derivation relationships of Canadian place names achieves an accuracy rate of 98.5% and a recall rate of 93.4%, and the reasoning results can effectively improve the accuracy of query results. The research enriches the theoretical framework of spatio-temporal derivation relationships of place names, solves the current problems of unclear definition and inability to automatically identify spatio-temporal derivation relationships, and provides new perspectives and tools for the application practice in the field of geographical information science.

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Publication Details

Journal
ISPRS International Journal of Geo-Information
Published
2024-09-13
DOI
https://doi.org/10.3390/ijgi13090327
Citations
3
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
5.87

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article

Construction and Inference Method of Semantic-Driven, Spatio-Temporal Derivation Relationship Network for Place Names

Wenjuan Lu, Wenjie Dong, Jizhou Wang, Xi Mao et al.
3 citations
ISPRS International Journal of Geo-Information
Geographic Information Systems Studies
5.87
article

Construction and Inference Method of Semantic-Driven, Spatio-Temporal Derivation Relationship Network for Place Names

Wenjuan Lu, Wenjie Dong, Jizhou Wang, Xi Mao, Yao Cheng
article en
3 citations

Abstract

As the proper noun for geographical entities, place names provide an intuitive way to identify and access specific geographic locations, playing a key role in semantic expression and spatial retrieval. However, existing research has insufficiently explored the spatio-temporal derivation relationships of place names, failing to fully utilize these relationships to enhance the connectivity between place names and improve spatial retrieval capabilities. Therefore, this paper conducts research on the spatio-temporal derivation relationships of place names, defines them in a standardized manner, clarifies the boundary conditions and identification methods, and then constructs a spatio-temporal derivation network of place names for expression and uses this network to carry out reasoning research on spatial adjacency relationships. Experiments and results showed that using the theory and methods of this paper to identify the spatio-temporal derivation relationships of Canadian place names achieves an accuracy rate of 98.5% and a recall rate of 93.4%, and the reasoning results can effectively improve the accuracy of query results. The research enriches the theoretical framework of spatio-temporal derivation relationships of place names, solves the current problems of unclear definition and inability to automatically identify spatio-temporal derivation relationships, and provides new perspectives and tools for the application practice in the field of geographical information science.

ISPRS International Journal of Geo-InformationVol. 13(9)
Chinese Academy of Surveying and Mapping (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 4%
Geographic Information Systems Studies
5.87
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