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.
Highlights
The importance of spatial information retrieval is increasing, and web map services attract a wide range of users
The non-query expansion method, the conventional information entropy-based query expansion method, and the semantic-based query expansion method proposed in this study were compared
This higher precision occurs because the query is expanded for a second time in the query expansion process based on the extended concepts obtained by analyzing the similarities between semantic properties based on the OSM ontology model
Summary
The importance of spatial information retrieval is increasing, and web map services attract a wide range of users. The Baidu map service in 2015 had 302 million monthly active users in China, and queries using the Baidu map service to retrieve living services accounted for 40% of the total search volume [1]. The proportion of people engaging in spatial information retrieval activities who are untrained has increased substantially [2]. These nonprofessional users generally use simple keywords to search for information. Providing users with an intelligent, efficient way to allow them to complete their queries with a few relevant keywords is a key issue that researchers in the information retrieval field around the globe are highly focused on addressing [4]
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