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Composing Cardinal Direction Relations Basing on Interval Algebra

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Knowledge Science, Engineering and Management (KSEM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6291))

Abstract

Direction relations between extended spatial objects are important commonsense knowledge. Skiadopoulos proposed a formal model for representing direction relations between compound regions (the finite union of simple regions), known as SK-model. It perhaps is currently one of most cognitive plausible models for qualitative direction information, and has attracted interests from artificial intelligence and geographic information system. Originating from Allen first using composition table to process time interval constraints; composing has become the key technique in qualitative spatial reasoning to check the consistency. Due to the massive number of basic directions in SK-model, its composition becomes extraordinary complex. This paper proposed a novel algorithm for the composition. Basing the concepts of smallest rectangular directions and its original directions, it transforms the composition of basic cardinal direction relations into the composition of interval relations corresponding to Allen’s interval algebra. Comparing with existing methods, this algorithm has quite good dimensional extendibility, that is, it can be easily transferred to the tridimensional space with a few modifications.

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References

  1. Cohn, A.G., Hazarika, S.M.: Qualitative spatial representation and reasoning: An overview. Fundamenta Informaticae 46(1), 2–32 (2001)

    MathSciNet  Google Scholar 

  2. Egenhofer, M.J.: Spherical Topological Relations. Journal on Data Semantics 3(1), 25–49 (2005)

    Article  Google Scholar 

  3. Renz, J.: Qualitative Spatial Reasoning with Topological Information. LNCS (LNAI), vol. 2293. Springer, Heidelberg (2002)

    MATH  Google Scholar 

  4. Andrew, U.F.: Qualitative spatial reasoning about cardinal directions. In: Proc. of 7th Austrian Conference on Artificial Intelligence, pp. 157–167. Morgan Kaufmann, Baltimore (1991)

    Google Scholar 

  5. Christian, F.: Using orientation information for qualitative spatial reasoning. In: Frank, A.U., Formentini, U., Campari, I. (eds.) GIS 1992. LNCS, vol. 639, pp. 162–178. Springer, Heidelberg (1992)

    Google Scholar 

  6. Goyal, R.K., Egenhofer, M.J.: Consistent Queries over Cardinal Directions across Different Levels of Detail. In: Proc. of 11th Int. Workshop on Database and Expert Systems Applications, Greenwich, London, UK, pp. 876–880. IEEE Press, Los Alamitos (2000)

    Chapter  Google Scholar 

  7. Goyal, R.K., Egenhofer, M.J.: Similarity of Cardinal Directions. In: Jensen, C.S., Schneider, M., Seeger, B., Tsotras, V.J. (eds.) SSTD 2001. LNCS, vol. 2121, pp. 36–55. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Skiadopoulos, S., Koubarakis, M.: Composing cardinal direction relations. Artificial Intelligence 152(1), 143–171 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  9. Skiadopoulos, S., Koubarakis, M.: On the consistency of cardinal direction constraints. Artificial Intelligence 163(1), 91–135 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  10. Cicerone, S., Felice, P.D.: Cardinal directions between spatial objects: the pairwise-consistency problem. Information Sciences 164(1), 165–188 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  11. Clementini, E., Felice, P., Hernandez, D.: Qualitative representation of positional information. Artificial Intelligence 95(2), 317–356 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  12. Liu, J.: A method of spatial reasoning based on qualitative trigonometry. Artificial Intelligence (1-2), 137–168 (1998)

    Google Scholar 

  13. Sistla, A.P., Bu, C.: Reasoning about qualitative spatial relationships. Journal of Automated Reasoning 25(4), 291–328 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  14. Gerevini, A., Renz, J.: Combining topological and size information for spatial reasoning. Artificial Intelligence 137(1), 1–42 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  15. Li, S.: Combining Topological and Directional Information for Spatial Reasoning. In: Proc. of Int. Joint Conf. on Artificial Intelligence, Hyderabad, India, pp. 435–440 (2007)

    Google Scholar 

  16. Allen, J.: Maintaining Knowledge about Temporal Intervals. Communications of the ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  17. Balbiani, P., Condotta, J.-F., Fariñas del Cerro, L.: A new Tractable Subclass of the Rectangle Algebra. In: Proc. of Int. Joint Conf. on Artificial Intelligence, Stockholm, Sweden, pp. 442–447 (1999)

    Google Scholar 

  18. Balbiani, P., Condotta, J.-F., Fariñas del Cerro, L.: Tractability results in the block algebra. Journal of Logic and Computation 12(5), 885–909 (2002)

    Article  MATH  MathSciNet  Google Scholar 

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Chen, J., Jia, H., Liu, D., Zhang, C. (2010). Composing Cardinal Direction Relations Basing on Interval Algebra. In: Bi, Y., Williams, MA. (eds) Knowledge Science, Engineering and Management. KSEM 2010. Lecture Notes in Computer Science(), vol 6291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15280-1_13

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  • DOI: https://doi.org/10.1007/978-3-642-15280-1_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15279-5

  • Online ISBN: 978-3-642-15280-1

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