A Semantic Expansion Model for VGI Retrieval
| Autor: | Hang Shen, Lin Li, Tao Sun, Yu Liu, Hui Xia |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
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 |
| Zdroj: | ISPRS International Journal of Geo-Information Volume 8 Issue 12 |
| ISSN: | 2220-9964 |
| DOI: | 10.3390/ijgi8120589 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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