Wenjie Dong
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Wenjie Dong has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jizhou Wang
Chinese Academy of Surveying and mapping; Beijing 100036; China, China
1 shared publication - Wenjuan Lu
School of Artificial Intelligence, China University of Geosciences, Beijing 100083, China
1 shared publication - Xi Mao
Institute of Geographic Information System and Cartography, Chinese Academy of Surveying and Mapping, Beijing 100036, China
1 shared publication - Yao Cheng
Chinese Academy of Surveying and Mapping, Beijing 100036, China
1 shared publication
Latest Publications
- Open Access
- 13 September 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (9) , 327
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.
- 13 September 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (9) , 327
Open AccessConstruction 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.