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Geographic Knowledge Extraction and Semantic Similarity in OpenStreetMap
Date Issued
2012-10
Date Available
2013-10-01T03:00:08Z
Abstract
In recent years, a web phenomenon known as Volunteered Geographic Information (VGI) has produced large crowdsourced geographic data sets. OpenStreetMap (OSM), the leading VGI project, aims at building an open-content world map through user contributions. OSM semantics consists of a set of properties (called 'tags') describing geographic classes, whose usage is defined by project contributors on a dedicated Wiki website. Because of its simple and open semantic structure, the OSM approach often results in noisy and ambiguous data, limiting its usability for analysis in information retrieval, recommender systems and data mining. Devising a mechanism for computing the semantic similarity of the OSM geographic classes can help alleviate this semantic gap. The contribution of this paper is twofold. It consists of (1) the development of the OSM Semantic Network by means of a web crawler tailored to the OSM Wiki website; this semantic network can be used to compute semantic similarity through co-citation measures, providing a novel semantic tool for OSM and GIS communities; (2) a study of the cognitive plausibility (i.e. the ability to replicate human judgement) of co-citation algorithms when applied to the computation of semantic similarity of geographic concepts. Empirical evidence supports the usage of co-citation algorithms-SimRank showing the highest plausibility-to compute concept similarity in a crowdsourced semantic network.
Sponsorship
Science Foundation Ireland
Other Sponsorship
StrategicResearch Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan
Type of Material
Journal Article
Publisher
Springer
Journal
Knowledge and Information Systems
Volume
37
Issue
1
Start Page
61
End Page
81
Copyright (Published Version)
2012 Springer-Verlag London
Language
English
Status of Item
Peer reviewed
ISSN
0219-1377
This item is made available under a Creative Commons License
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2012_-_Geographic_Knowledge_Extraction_and_Semantic_Similarity_in_OpenStreetMap_-_Ballatore_et_al.pdf
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