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A Semantic Expansion Model for VGI Retrieval
- Source :
- ISPRS International Journal of Geo-Information, Volume 8, Issue 12
- Publication Year :
- 2019
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2019.
-
Abstract
- OpenStreetMap (OSM) is a representative volunteered geographic information (VGI) project. However, there have been difficulties in retrieving spatial information from OSM. Ontology is an effective knowledge organization and representation method that is often used to enrich the search capabilities of search systems. This paper constructed an OSM ontology model with semantic property items. A query expansion method is also proposed based on the similarity of properties of the ontology model. Moreover, a relevant experiment is conducted using OSM data related to China. The experimental results demonstrate that the recall and precision of the proposed method reach 80% and 87% for geographic information retrieval, respectively. This study provides a method that can be used as a reference for subsequent research on spatial information retrieval.
- Subjects :
- Volunteered geographic information
Information retrieval
Computer science
Knowledge organization
Geography, Planning and Development
geographical information retrieval
sematic similarity
02 engineering and technology
Ontology (information science)
Geographic information retrieval
OSM ontology
Query expansion
020204 information systems
query expansion
Similarity (psychology)
0202 electrical engineering, electronic engineering, information engineering
Earth and Planetary Sciences (miscellaneous)
020201 artificial intelligence & image processing
Computers in Earth Sciences
Precision and recall
Spatial analysis
Subjects
Details
- Language :
- English
- ISSN :
- 22209964
- Database :
- OpenAIRE
- Journal :
- ISPRS International Journal of Geo-Information
- Accession number :
- edsair.doi.dedup.....35b95fd37314aeb89b245182bb7e71b0
- Full Text :
- https://doi.org/10.3390/ijgi8120589