Advertisement

Graph-Based Navigation Strategies for Heterogeneous Spatial Data Sets

  • Andrea Rodríguez
  • Francisco Godoy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4197)

Abstract

Querying heterogeneous spatial databases involves not only characterizing and comparing the information content of several databases, but also navigating or accessing the data sets with the query answer. This work proposes a formalism that relates the information content of data sets by three basic types of correspondence relations: data equivalence, difference of data omission, and difference of data commission. These correspondence relations define the information space over which a navigation process is carried out. Based on a complete or an incomplete information space, this work proposes strategies that optimize the retrieval process of information coming from different databases. The results of this study show the advantages of defining the information space to select and access databases. In particular, strategies that estimate the information contribution of data sets based on correspondence relations outperform a strategy that considers a random list or a list of data sets sorted by size.

Keywords

Equivalent Region Retrieval Process Query Result Spatial Database Information Space 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)Google Scholar
  3. 3.
    Cutting, D., Karger, D., Oederson, J.: Constant interaction-time scatter/gather browsing of very large document collection. In: 16th Annual International ACM/SIGIR Conference, pp. 126–135 (1993)Google Scholar
  4. 4.
    Egenhofer, M., Clementini, E., Di Felice, P.: Evaluating inconsistency among multiple representations. In: Spatial Data Handling, Edinburg, Scotland, pp. 901–920 (1994)Google Scholar
  5. 5.
    Egenhofer, M., Sharma, J.: Assessing the consistency of complete and incomplete topological information. Geographical Systems 1(1), 47–68 (1993)Google Scholar
  6. 6.
    Flowerdew, R.: Spatial Data Integration, pp. 375–387. Longman Scientific & Technical (1991)Google Scholar
  7. 7.
    Fonseca, F., Egenhofer, M., Agouris, P., Camara, C.: Using ontologies for integrated information systems. Transactions in GIS 6(3), 231–257 (2002)CrossRefGoogle Scholar
  8. 8.
    Rodríguez, A., Egenhofer, M.: Determining semantic similarity among entity classes from different ontologies. IEEE Transactions on Knowledge and Data Engineering 15(2), 442–456 (2003)CrossRefGoogle Scholar
  9. 9.
    Kashyap, V., Sheth, A.: Schematic and semantic similarities between batabase objects: A context-based approach. The Very Large Database Journal 5(4), 276–304 (1996)CrossRefGoogle Scholar
  10. 10.
    Kuipers, B., Paredaens, J., den Busshe, J.: On topological equivalence of spatial databases. In: Afrati, F.N., Kolaitis, P.G. (eds.) ICDT 1997. LNCS, vol. 1186, pp. 432–446. Springer, Heidelberg (1996)Google Scholar
  11. 11.
    Mackworth, A.: Consistency in networks of relations. Artificial Intelligence 8(1), 99–118 (1977)MATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Mena, E., Illarramendi, A.: Ontology-Based Query Processing for Global Information Systems. Kluwer Academic Publishers, Norwell (2001)Google Scholar
  13. 13.
    Ram, S., Shankaranarayanan, G.: Modeling and navigation of large information spaces: A semantic based approach. In: International Conference on System Science. IEEE CS Press, Los Alamitos (1999), http://computer.org/proceedings/hicss/0001/00016/00016020abs.htm Google Scholar
  14. 14.
    Roussinov, D., McQuaid, M.: Information navigation by clustering and summary query results. In: International Conference on System Sciences, p. 3006. IEEE CS Press, Los Alamitos (2000)Google Scholar
  15. 15.
    Sheth, A.: Changing Focus on Interoperability in Information Systems: From System, Syntax, Structure to Semantics. In: Interoperating Geographic Information Systems, pp. 5–30. Kluwer Academic Publishers, Dordrecht (1999)Google Scholar
  16. 16.
    VIVISMO (2006), http://vivismo.com
  17. 17.
    Weinstein, P., Birmingham, P.: Comparing concepts in differentiated ontologies. In: 12th Workshop on Knowledge Adquisition, Modeling, and Management, Banff, Canada (1999)Google Scholar
  18. 18.
    Worboys, M., Clementini, E.: Integration of imperfect spatial information. Journal of Visual Languages and Computing 12, 61–80 (2001)CrossRefGoogle Scholar
  19. 19.
    Yahoo! (2006), http://www.yahoo.com
  20. 20.
    Zamir, O., Etzioni, O.: Grouper: A dynamic cluster interface to web search results. In: WWW8 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andrea Rodríguez
    • 1
  • Francisco Godoy
    • 2
  1. 1.Department of Computer ScienceUniversity of ConcepciónConcepciónChile
  2. 2.Center for Oceanographic Research in the Eastern South-Pacific, FONDAP-COPASUniversity of ConcepciónConcepciónChile

Personalised recommendations