Global Positioning System Reference
In-Depth Information
In this chapter we also presented the ontology created to represent the
necessary information to support the touristic application. The ontology is
aligned with LinkedGeoData, TimeOntology and WGS_84 ontologies.
The contribution of this chapter is to show the architecture to integrating
a personalization system and a GIS in a smartphone application that runs
entirely off-line. These features are still missing in most of the Android
location-based applications. The research presented demonstrates that: a)
it is possible to work with geographic data in a smartphone even without
spatial databases being adapted to Android; b) it is possible to perform
routing functionalities off-line in a smartphone. Additionally it is showed
that, so far, it is not effi cient to use Semantic Web technologies in an
Android device. It is important to note that the system looks for a total
tourist experience, taking into account restaurants, monuments, cinemas,
theaters, shopping centers, etc. as well as the opening times, timetables
and visiting times.
The chapter presented a proof of concept that shows the application
works properly when data about POI is known, correct and complete.
The proof of concept also shows that the visit time of a single POI may be
variable according to the nature of the POI itself or the kind of user who is
traveling, and so should be taken into account in a recommender system
like ours.
As further work there are three main goals: to achieve efficient
GeoSPARQL queries for bigger datasets, thus, to have a scalable system in
order to develop the prototype with GeoSPARQL queries into a true end-
user application; to improve the data model of POI to take into account
different times to visit them and timetables; and to develop a true usable
end-user application.
Acknowledgments
This work has been partially supported by the Ministerio de Industria
under project AVANZA2 IST-020110-2009-442 and by the Ministerio de
Educación y Ciencia and FEDER under project TIN2008-00444/TIN, Grupo
Consolidado.
References
Aduna. 2012. Sesame. Available at: http://www.openrdf.org [Accessed September 19,
2012].
Adomavicius, G. and A. Tuzhilin. 2011. Context Aware Recommender Systems. In:
Recommender Systems. Handbook, Springer Science, pp. 217-253.
Battle, R. and D. Kolas. 2011. GeoSPARQL: Enabling a Geospatial Semantic Web. Semantic
Web-Interoperability, Usability, Aplicatibility 0(0): 1-17. Available at: http://semantic-
web-journal.org/sites/default/fi les/swj176_1.pdf [Accessed March 11, 2013].
Search WWH ::
Custom Search