Skip to main content
SpringerLink
Log in

Spatial reasoning using symbolic arrays

  • Technical Papers
  • Conference paper
  • First Online:
Theories and Methods of Spatio-Temporal Reasoning in Geographic Space

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 639))

Abstract

Research in Artificial Intelligence and Cognitive Science has suggested the distinction between visual knowledge (such as shape, volume and colour of objects) and spatial knowledge (that is, spatial relationships among the different objects of a visual scene). We find this distinction applicable to Information Systems concerned with spatial reasoning and especially to Geographic Information Systems. In particular, this paper deals with the representation of spatial information in GIS. The paper presents a representational formalism which captures the knowledge embedded in spatial relationships and provides the ability to represent, retrieve and reason about spatial information not explicitly stored in memory.

Research partially supported by the National Science Foundation under Grant IRI-9057573 (PYI Award), by DEC and Bellcore, and by UMIACS.

On-leave from the Dept. of Computer Science, University of Maryland, College Park, U.S.A.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baddeley,A.D., & Lieberman,K. (1980) Spatial Working Memory. In R. Nickerson (Ed.) Attention and Performance VIII. Erblaum.

    Google Scholar 

  2. Bauer,R.M., & Rubens,A.B. (1985) Agnosia, In Heilman & Valenstein (Eds.), Clinical Neuropsychology. Oxford University Press.

    Google Scholar 

  3. Biedennan, I. (1987) Recognition by Components; A Theory of Human Image Understanding. Psychological Review, 94.

    Google Scholar 

  4. Cai, Y., Cercone, N., Han, J. (1990) Learning Characteristic Rules from Relational Databases. Computational Intelligence, 11.

    Google Scholar 

  5. Chang,S., Erland, J., Li, Y. (1989) The Design of Pictorial Database upon the Theory of Symbolic Projections. In the proceedings of the First Symposium on the Design and Implementation of Large Spatial Databases (SSD 89).

    Google Scholar 

  6. Frank,A.U., Barrera,R. (1989) The Fieldtree: A Data Structure for Geographic Information Systems. In the proceedings of the First Symposium on the Design and Implementation of Large Spatial Databases (SSD 89).

    Google Scholar 

  7. Glasgow,J.I. (1990) Artificial Intelligence and Imagery. Proceedings of the second IEEE conference on Tools for AI.

    Google Scholar 

  8. Glasgow,J.I., Fortier,S & Allen,F.H. (1991) Crystal and Molecular Structure Determination through Imagery, In Hunter (Ed.), Artificial Intelligence and Molecular Biology, AAAI Press. Also appears in the Proceedings of the Seventh IEEE Conference on Artificial Intelligence Applications.

    Google Scholar 

  9. Glasgow,J.I & Papadias,D. (?) Computational Imagery. To appear in the Cognitive Science Journal.

    Google Scholar 

  10. Larkin,J. & Simon,H.A. (1987) Why a Diagram is (sometimes) Worth Ten Thousand Words. Cognitive Science, 10.

    Google Scholar 

  11. Lindsay,R.K. (1988) Images and Inference. Cognition, 29.

    Google Scholar 

  12. Marr,D. (1982) Vision: A Computational Investigation in the Human Representation of Visual Information, San Francisco, Freeman.

    Google Scholar 

  13. McDermott,D.V.& Davis,E. (1984) Planning Routes through Uncertain Territory. Artificial Intelligence, 22.

    Google Scholar 

  14. Papadias,D. & Glasgow,J.I. (1991) A Knowledge Representation Scheme for Computational Imagery. Proceedings of the 13th Annual Conference of the Cognitive Science Society, Lawrence Erblaum Associates.

    Google Scholar 

  15. Raphael,B. (1971) The Frame Problem in Problem Solving Systems. In Findler and Meltzer (Eds.), Artificial Intelligence and Heuristic Programming, Edinburgh University Press.

    Google Scholar 

  16. Samet,H. (1989) The Design and Analysis of Spatial Data Structures. Addison Wesley.

    Google Scholar 

  17. Sellis,T., Roussopoulos,N., Faloutsos,C. (1987) The R+-tree: A Dynamic Index for Multi-Dimensional Objects. In P. Stocker and W. Kent (eds.) 13th VLDB conference, Brighton, England.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Division Department of Electrical and Computer Engineering, National Technical University of Athens, 157 73, Zographou, Athens, Greece

    Dimitris Papadias & Timos Sellis

Authors
  1. Dimitris Papadias
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Timos Sellis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

A. U. Frank I. Campari U. Formentini

Rights and permissions

Reprints and permissions

Copyright information

© 1992 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Papadias, D., Sellis, T. (1992). Spatial reasoning using symbolic arrays. In: Frank, A.U., Campari, I., Formentini, U. (eds) Theories and Methods of Spatio-Temporal Reasoning in Geographic Space. Lecture Notes in Computer Science, vol 639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55966-3_9

Download citation

  • DOI: https://doi.org/10.1007/3-540-55966-3_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55966-5

  • Online ISBN: 978-3-540-47333-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation