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Open AccessArticle

A Semantic Expansion Model for VGI Retrieval

by Tao Sun 1, Hui Xia 2, Lin Li 1,3,4,*, Hang Shen 1 and Yu Liu 1
1
School of Resource and Environment Sciences, Wuhan University, Wuhan 430079, China
2
Changjiang Spatial Information Technology Engineering CO, LTD, Wuhan 430079, China
3
The Key Laboratory for Geographical Information Systems, Ministry of Education, Wuhan 430079, China
4
Geo Spatial Information Science Collaborative Innovation Center of Wuhan University, 129 Luoyu Rd., Wuhan 430079, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(12), 589; https://doi.org/10.3390/ijgi8120589
Received: 19 October 2019 / Revised: 2 December 2019 / Accepted: 16 December 2019 / Published: 17 December 2019
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. View Full-Text
Keywords: geographical information retrieval; OSM ontology; sematic similarity; query expansion geographical information retrieval; OSM ontology; sematic similarity; query expansion
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Sun, T.; Xia, H.; Li, L.; Shen, H.; Liu, Y. A Semantic Expansion Model for VGI Retrieval. ISPRS Int. J. Geo-Inf. 2019, 8, 589.

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