Abstract
Geographical data is obtained through abstractions made from objects in the real world. Generally, each of these abstractions is obtained by taking into account only one point of view about the object being analyzed. When different abstractions are made on the same object different data sources regarding to it are produced. These data sources are generally heterogeneous. Thus the semantic processing of these objects become challenge since different data sources must be combined to obtain good results in tasks such as information retrieval and analysis for decision-making. This paper presents an approach based on ontologies to enrich the semantic representation of geospatial objects taking into account different abstractions made on them. The experimental results show the usefulness of this approach and how it is possible to make a multidimensional semantic representation automatically using classification algorithms and search techniques on trees.
Chapter PDF
Similar content being viewed by others
References
Gärdenfors, P.: Conceptual spaces as a framework for knowledge representation. Mind and Matter 2, 9–27 (2004)
Raubal, M.: Formalizing Conceptual Spaces. Formal Ontology in Information Systems. In: Proceedings of the Third International Conference (FOIS 2004), p. 114 (2004)
Carmagnola, F., et al.: A Semantic Framework for Adaptive web-based Systems. In: Proceedings of the 9th Conference on Advances in Artificial Intelligence, pp. 370–380 (2005)
Balley, S., Parent, C., Spaccapietra, S.: Modelling geographic data with multiple representations. International Journal of Geographical Information Science 18, 329–354 (2004)
Adnani, M.E., Yétongnon, K., Benslimane, D.: A multiple layered functional data model to support multiple representations and interoperability of GIS: application to urban management systems. In: Proceedings of the 9th ACM International Symposium on Advances in Geographic Information Systems, pp. 70–75 (2001)
Strang, T., Linnhoff-Popien, C., Frank, K.: CoOL: A Context Ontology Language to Enable Contextual Interoperability. In: Stefani, J.-B., Demeure, I., Zhang, J. (eds.) DAIS 2003. LNCS, vol. 2893, pp. 236–247. Springer, Heidelberg (2003)
Ahlqvist, O.: A Parameterized Representation of Uncertain Conceptual Spaces. Transactions in GIS 8(4), 493–514 (2004)
Larin-Fonseca, R., Garea-Llano, E.: Automatic Representation of Geographical Data from Semantic Point of View throughout a New Ontology and Classification Techniques. Transaction in GISÂ 15(1) (2011)
Jaccard, P.: Étude comparative de la distribution florale dans une portion des Alpes et des Jura. Bulletin de la Société Vaudoise des Sciences Naturelles 37, 547–579 (1901)
MATLAB, version 7.10.0 (R2010a). The MathWorks Inc., Natick (2010)
Duin, R.P.W., et al.: PRTools4 A Matlab Toolbox for Pattern Recognition Version 4.1.5. Delft Pattern Recognition Research, Faculty EWI - ICT, Delft University of Technology, The Netherlands (2009), http://prtools.org
Duin, R.P.W., et al.: DisTools A Matlab Toolbox for Pattern Recognition Delft Pattern Recognition Research, Faculty EWI - ICT, Delft University of Technology, The Netherlands (2009), http://prtools.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fonseca, R.L., Llano, E.G. (2012). Semantic Representation of Geospatial Objects Using Multiples Knowledge Domains. In: Alvarez, L., Mejail, M., Gomez, L., Jacobo, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2012. Lecture Notes in Computer Science, vol 7441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33275-3_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-33275-3_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33274-6
Online ISBN: 978-3-642-33275-3
eBook Packages: Computer ScienceComputer Science (R0)