Abstract
Mobile user location data has been commercially exploited and studied due to the commoditization of GPS position sensors and the popularity of Location Based Services (LBS). Context researchers have already studied how to understand human mobility using location histories [1], and how to model location context using ontologies [2]. However, these studies make surprisingly little use of rich geospatial data and knowledge about the world to a) explicitly describe user locations, and b) possibly infer implicit contexts. In this paper, we demonstrate that openly accessible geospatial data can facilitate both a) and b), thus resulting in improved understanding of mobile user location context.
Chapter PDF
Similar content being viewed by others
References
González, M.C., Hidalgo, C.A., Barabási, A.-L.: Hidalgo, and Albert-László Barabási: Understanding Individual Human Mobility Patterns. Nature 453, 779–782 (2008)
Chen, H., Finin, T., Joshi, A.: An Ontology for Context-Aware Pervasive Computing Environments. Special Issue on Ontologies for Distributed Systems, Knowledge Engineering Review 18, 197–207 (2004)
Stadler, C., Lehmann, J., Höffner, K., Auer, S.: LinkedGeoData: A Core for a Web of Spatial Open Data. Semantic Web Journal (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shangguan, Z., McGuinness, D.L. (2013). Deciphering Location Context – A Semantic Web Approach. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds) The Semantic Web: ESWC 2013 Satellite Events. ESWC 2013. Lecture Notes in Computer Science, vol 7955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41242-4_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-41242-4_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41241-7
Online ISBN: 978-3-642-41242-4
eBook Packages: Computer ScienceComputer Science (R0)