Simplifying Sets of Events by Selecting Temporal Relations

  • Andrea Rodríguez
  • Nico Van de Weghe
  • Philippe De Maeyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3234)


Reasoning about events or temporal aspects is fundamental for modeling geographic phenomena. This work concerns the analysis of events as configurations of temporal intervals. It presents two strategies to select relations that characterize configurations of temporal intervals: a strategy based on the algebraic property of composition and a strategy based on a neighboring concept in a vector representation. This type of analysis is useful for characterizing sets of events without the need of making an exhaustive specification of all temporal relations. This work complements a previous study about topological relations of regions in a 2D space and confirms the potential of using the algebraic properties of composition and the metric characteristics of intervals, even if only qualitative relations are considered.


Temporal Interval Binary Relation Temporal Relation Delaunay Triangulation Constraint Satisfaction Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Allen, J.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 823–843 (1983)CrossRefGoogle Scholar
  2. 2.
    Claramunt, C., Jiang, B.: An integrated representation of spatial and temporal relations between evolving regions. Geographical Systems 3(4), 411–428 (2001)CrossRefGoogle Scholar
  3. 3.
    Clementi, E., Sharma, J., Egenhofer, M.: Modelling topological spatial relations strategies for query languages. Computing and Graphics 18(6), 815–822 (1994)CrossRefGoogle Scholar
  4. 4.
    Egenhofer, M.: Deriving the composition of binary topological relations. Journal of Visual Languages and Computing 5(2), 133–149 (1994)CrossRefGoogle Scholar
  5. 5.
    Egenhofer, M.: Query preprocessing in spatial query by sketch. Journal of Visual Computing 8(4), 403–424 (1997)CrossRefGoogle Scholar
  6. 6.
    Egenhofer, M., Sharma, J.: Assessing the consistency of complete and incomplete topological information. Geographical Systems 1, 47–68 (1993)Google Scholar
  7. 7.
    Florence, J., Egenhofer, M.: Distribution of topological relations in geographic databases. In: ACSM/ASPRS, Baltimore, MD (1996)Google Scholar
  8. 8.
    Freksa, C.: Temporal reasoning based on semi intervals. Artificial Intelligence 54, 199–227 (1992)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Hamblin, C.: Instants and intervals. Studium Generale 24, 127–134 (1971)Google Scholar
  10. 10.
    Humberstone, I.: Interval semantics for tense logic: Some remarks. Journal of Philosophical Logic 8, 171–196 (1979)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Kriegel, H., Brinkhoff, T.: Efficient spatial query processing. IEEE Data Engineering Bulletin 16(3), 10–15 (1993)Google Scholar
  12. 12.
    Kulpa, Z.: Diagrammatic representation for a space of intervals. Machine Graphics 6(1), 5–24 (1997)MathSciNetGoogle Scholar
  13. 13.
    Langran, G.: Temporal GIS design tradeoffs. Journal of URISA 2(2), 16–25 (1990)Google Scholar
  14. 14.
    Mackworth, A.: Consistency in networks of relations. Artificial Intelligence 8(1), 99–118 (1977)zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Maddux, R.: Some Algebras and Algorithms for Reasoning about Time and Space. Technical report, Department of Mathematics, IOWA State University, Ames, IO (1990)Google Scholar
  16. 16.
    Meseguer, P.: Constraint satisfaction problems: an overview. Artificial Intelligence Communications AICOM 2(1), 3–17 (1989)Google Scholar
  17. 17.
    O’Rouke, J.: Computational Geometry. Cmabridge University Press, Cambridge (1993)Google Scholar
  18. 18.
    Preparata, F., Shamos, M.: Computational Geometry: An Introduction. Springer, Berlin (1985)Google Scholar
  19. 19.
    Ramachandran, B., MacLeod, F.: Modelling temporal changes in GIS using an object-oriented approach. In: Proceedings of the Sixth International Symposium on Spatial Data Handling, Edinburgh, Scotland, pp. 518–537 (1994)Google Scholar
  20. 20.
    Rodríguez, A., Egenhofer, M., Blaser, A.: Query pre-processing of topological constraints: Comparing composition-based with neighborhood-based approach. In: Hadzilacos, T., Manolopoulos, Y., Roddick, J., Theodoridis, Y. (eds.) SSTD 2003. LNCS, vol. 2750, pp. 362–379. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  21. 21.
    Ross, S.: A First Course in Probability. Macmillan, Basingstoke (1976)zbMATHGoogle Scholar
  22. 22.
    Stock, O.: Spatial and Temporal Reasoning. Kluwer Academic Publishers, Dordrecht (1997)CrossRefGoogle Scholar
  23. 23.
    Tarski, A.: On the calculus of relations. Journal of Symbolic Logic 6(3), 73–89 (1941)zbMATHCrossRefMathSciNetGoogle Scholar
  24. 24.
    Tobler, W.: A computer movie simulating urban growth in the detroit region. Economic Geography 46(2), 234–240 (1970)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Andrea Rodríguez
    • 1
  • Nico Van de Weghe
    • 2
  • Philippe De Maeyer
    • 2
  1. 1.Department of Computer ScienceUniversity of Concepción , Center for Web Research, University of ChileChile
  2. 2.Department of GeographyGhent UniversityBelgium

Personalised recommendations