Sim-DL: Towards a Semantic Similarity Measurement Theory for the Description Logic \(\mathcal ALCNR\) in Geographic Information Retrieval

  • Krzysztof Janowicz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4278)


Similarity measurement theories play an increasing role in GIScience and especially in information retrieval and integration. Existing feature and geometric models have proven useful in detecting close but not identical concepts and entities. However, until now none of these theories are able to handle the expressivity of description logics for various reasons and therefore are not applicable to the kind of ontologies usually developed for geographic information systems or the upcoming geospatial semantic web. To close the resulting gap between available similarity theories on the one side and existing ontologies on the other, this paper presents ongoing work to develop a context-aware similarity theory for concepts specified in expressive description logics such as \(\mathcal ALCNR\).


Information Retrieval Description Logic Similarity Theory Concept Description Primitive Concept 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lutz, M., Klien, E.: Ontology-Based Retrieval of Geographic Information. International Journal of Geographical Information Science 20(3), 233–260 (2006)CrossRefGoogle Scholar
  2. 2.
    Janowicz, K.: Towards a Similarity-Based Identity Assumption Service for Historical Places. In: Raubal, M., Miller, H.J., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2006. LNCS, vol. 4197, pp. 199–216. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Raubal, M.: Formalizing Conceptual Spaces, in Formal Ontology in Information Systems. In: Varzi, A., Vieu, L. (eds.) Proceedings of the Third International Conference (FOIS 2004), pp. 153–164. IOS Press, Amsterdam (2004)Google Scholar
  4. 4.
    Rodríguez, A.M., Egenhofer, M.J.: Comparing Geospatial Entity Classes: An Asymmetric and Context-Dependent Similarity Measure. International Journal of Geographical Information Science 18(3), 229–256 (2004)CrossRefGoogle Scholar
  5. 5.
    Schwering, A., Raubal, M.: Measuring Semantic Similarity between Geospatial Conceptual Regions. In: Rodríguez, M.A., Cruz, I., Levashkin, S., Egenhofer, M.J. (eds.) GeoS 2005. LNCS, vol. 3799, pp. 90–106. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Goldstone, R., Son, J.: Similarity, in Cambridge Handbook of Thinking and Reasoning. In: Holyoak, K., Morrison, R. (eds.). Cambridge University Press, Cambridge (2004)Google Scholar
  7. 7.
    Schwering, A.: Semantic Similarity Measurement including Spatial Relations for Semantic Information Retrieval of Geo-Spatial Data. Institute for Geoinformatics, University of Münster, Germany, PhD Thesis (submitted, 2006) Google Scholar
  8. 8.
    Janowicz, K.: Extending Semantic Similarity Measurement by Thematic Roles. In: Rodríguez, M.A., Cruz, I., Levashkin, S., Egenhofer, M.J. (eds.) GeoS 2005. LNCS, vol. 3799, pp. 137–152. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  9. 9.
    Gärdenfors, P.: Conceptual Spaces - The Geometry of Thought, p. 307. Bradford Books, MIT Press, Cambridge (2000)Google Scholar
  10. 10.
    Schwering, A.: Hybrid Model for Semantic Similarity Measurement. In: 4th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2005), Springer, Agia Napa, Cyprus (2005)Google Scholar
  11. 11.
    Hau, J., Lee, W., Darlington, J.: A Semantic Similarity Measure for Semantic Web Services. In: Web Service Semantics Workshop 2005 at WWW 2005, Chiba, Japan (2005)Google Scholar
  12. 12.
    d’Amato, C., Fanizzi, N., Esposito, F.: A Semantic Dissimilarity Measure for Concept Descriptions in Ontological Knowledge Bases. In: The Second International Workshop on Knowledge Discovery and Ontologies, Porto, Portugal (2005)Google Scholar
  13. 13.
    Möller, R.: Expressive Description Logics: Foundations for Practical Applications. Habilitation Thesis. University of Hamburg, Computer Science Department, Germany (2001) Google Scholar
  14. 14.
    Borgida, A., Walsh, T.J., Hirsh, H.: Towards Measuring Similarity in Description Logics. In: International Workshop on Description Logics (DL 2005), Edinburgh, Scotland (2005)Google Scholar
  15. 15.
    Ehrig, M., et al.: Similarity for Ontologies - A Comprehensive Framework. In: 13th European Conference on Information Systems, Regensburg, Germany (2005)Google Scholar
  16. 16.
    Baader, F., Nutt, W.: Basic Description Logics. In: Baader, D.C.F., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.) The Description Logic Handbook, pp. 47–100. Cambridge University Press, Cambridge (2002)Google Scholar
  17. 17.
    Brandt, S., Küsters, R., Turhan, A.Y.: Approximating ALCN-Concept Descriptions. In: Proceedings of the 2002 International Workshop on Description Logics (2002)Google Scholar
  18. 18.
    Molitor, R.: Structural Subsumption for ALN. LTCS-Report 98-03, LuFG Theoretical Computer Science, RWTH Aachen, Germany (1998)Google Scholar
  19. 19.
    Lin, D.: An information-theoretic definition of similarity. In: Proceedings of the Fifteenth International Conference on Machine Learning, pp. 296–304. Morgan Kaufmann, San Francisco (1998)Google Scholar
  20. 20.
    Tversky, A.: Features of Similarity. Psychological Review 84(4), 327–352 (1977)CrossRefGoogle Scholar
  21. 21.
    Bruns, T.H., Egenhofer, M.J.: Similarity of Spatial Scenes. In: Kraak, M.-J., Molenaar, M. (eds.) Seventh International Symposium on Spatial Data Handling (SDH 1996), Delft, Netherlands, pp. 31–42 (1996)Google Scholar
  22. 22.
    Freksa, C.: Temporal Reasoning Based on Semi-Intervals. Artificial Intelligence 54(1), 199–227 (1992)CrossRefMathSciNetGoogle Scholar
  23. 23.
    Rada, R., et al.: Development and Application of a Metric on Semantic Nets. IEEE Transaction on Systems, Man, and Cybernetics 19(1), 17–30 (1989)CrossRefGoogle Scholar
  24. 24.
    Li, B., Fonseca, F.T.: TDD - A Comprehensive Model for Qualitative Spatial Similarity Assessment. Spatial Cognition and Computation 6(1), 31–62 (2006)CrossRefGoogle Scholar
  25. 25.
    Barsalou, L.: Situated simulation in the human conceptual system. Language and Cognitive Processes 5(6), 513–562 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Krzysztof Janowicz
    • 1
  1. 1.Institute for GeoinformaticsUniversity of MuensterGermany

Personalised recommendations