Knowledge Discovery Based Query Answering in Hierarchical Information Systems

  • Zbigniew W. Raś
  • Agnieszka Dardzińska
  • Osman Gürdal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3642)


The paper concerns failing queries in incomplete Distributed Autonomous Information Systems (DAIS) based on attributes which are hierarchical and which semantics at different sites of DAIS may differ. Query q fails in an information system S, if the empty set of objects is returned as an answer. Alternatively, query q can be converted to a new query which is solvable in S. By a refinement of q, we mean a process of replacing q by a new relaxed query, as it was proposed in [2], [7], and [8], which is similar to q and which does not fail in S. If some attributes listed in q have values finer than the values used in S, then rules discovered either locally at S or at other sites of DAIS are used to assign new finer values of these attributes to objects in S. Queries may also fail in S when some of the attributes listed in q are outside the domain of S. To resolve this type of a problem, we extract definitions of such attributes at some of the remote sites for S in DAIS and next use them to approximate q in S. In order to do that successfully, we assume that all involved information systems have to agree on the ontology of some of their common attributes [14], [15], [16]. This paper shows that failing queries can be often handled successfully if knowledge discovery methods are used either to convert them to new queries or to find finer descriptions of objects in S.


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  1. 1.
    Benjamins, V.R., Fensel, D., Pérez, A.G.: Knowledge management through ontologies, in. In: Proceedings of the 2nd International Conference on Practical Aspects of Knowledge Management (PAKM 1998), Basel, Switzerland (1998)Google Scholar
  2. 2.
    Chu, W., Yang, H., Chiang, K., Minock, M., Chow, G., Larson, C.: Cobase: A scalable and extensible cooperative information system. Journal of Intelligent Information Systems 6(2/3), 223–259 (1996)CrossRefGoogle Scholar
  3. 3.
    Dardzińska, A., Raś, Z.W.: Rule-Based Chase Algorithm for Partially Incomplete Information Systems. In: Tsumoto, S., Yamaguchi, T., Numao, M., Motoda, H. (eds.) AM 2003. LNCS (LNAI), vol. 3430, pp. 255–267. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Dardzińska, A., Raś, Z.W.: On Rules Discovery from Incomplete Information Systems. In: Lin, T.Y., Hu, X., Ohsuga, S., Liau, C. (eds.) Proceedings of ICDM 2003 Workshop on Foundations and New Directions of Data Mining, Melbourne, Florida, pp. 31–35. IEEE Computer Society, Los Alamitos (2003)Google Scholar
  5. 5.
    Dardzińska, A., Raś, Z.W.: Chasing Unknown Values in Incomplete Information Systems. In: Lin, T.Y., Hu, X., Ohsuga, S., Liau, C. (eds.) Proceedings of ICDM 2003 Workshop on Foundations and New Directions of Data Mining, Melbourne, Florida, pp. 24–30. IEEE Computer Society, Los Alamitos (2003)Google Scholar
  6. 6.
    Fensel, D.: Ontologies: a silver bullet for knowledge management and electronic commerce. Springer, Heidelberg (1998)Google Scholar
  7. 7.
    Gaasterland, T.: Cooperative answering through controlled query relaxation. IEEE Expert 12(5), 48–59 (1997)CrossRefGoogle Scholar
  8. 8.
    Godfrey, P.: Minimization in cooperative response to failing database queries. International Journal of Cooperative Information Systems 6(2), 95–149 (1997)CrossRefGoogle Scholar
  9. 9.
    Guarino, N. (ed.): Formal Ontology in Information Systems. IOS Press, Amsterdam (1998)Google Scholar
  10. 10.
    Guarino, N., Giaretta, P.: Ontologies and knowledge bases, towards a terminological clarification. In: Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing. IOS Press, Amsterdam (1995)Google Scholar
  11. 11.
    Pawlak, Z.: Rough sets-theoretical aspects of reasoning about data. Kluwer, Dordrecht (1991)MATHGoogle Scholar
  12. 12.
    Pawlak, Z.: Information systems - theoretical foundations. Information Systems Journal 6, 205–218 (1991)Google Scholar
  13. 13.
    Raś, Z.W.: Dictionaries in a distributed knowledge-based system. In: Concurrent Engineering: Research and Applications, Conference Proceedings, Concurrent Technologies Corporation, Pittsburgh, Penn., pp. 383–390 (1994)Google Scholar
  14. 14.
    Raś, Z.W., Dardzińska, A.: Ontology Based Distributed Autonomous Knowledge Systems. Information Systems International Journal 29(1), 47–58 (2004)Google Scholar
  15. 15.
    Raś, Z.W., Dardzińska, A.: Query answering based on collaboration and chase. In: Christiansen, H., Hacid, M.-S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2004. LNCS (LNAI), vol. 3055, pp. 125–136. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  16. 16.
    Raś, Z.W., Joshi, S.: Query approximate answering system for an incomplete DKBS. Fundamenta Informaticae Journal 30(3/4), 313–324 (1997)MATHGoogle Scholar
  17. 17.
    Sowa, J.F.: Ontology, metadata, and semiotics. In: Ganter, B., Mineau, G.W. (eds.) ICCS 2000. LNCS, vol. 1867, pp. 55–81. Springer, Heidelberg (2000a)CrossRefGoogle Scholar
  18. 18.
    Sowa, J.F.: Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks/Cole Publishing Co., Pacific Grove(2000b)Google Scholar
  19. 19.
    Sowa, J.F.: Ontological categories. In: Albertazzi, L. (ed.) Shapes of Forms: From Gestalt Psychology and Phenomenology to Ontology and Mathematics, pp. 307–340. Kluwer Academic Publishers, Dordrecht (1999a)Google Scholar
  20. 20.
    Suzuki, E., Kodratoff, Y.: Discovery of Surprising Exception Rules Based on Intensity of Implication. In: Żytkow, J.M. (ed.) PKDD 1998. LNCS (LNAI), vol. 1510. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  21. 21.
    Van Heijst, G., Schreiber, A., Wielinga, B.: Using explicit ontologies in KBS development. International Journal of Human and Computer Studies 46(2/3), 183–292 (1997)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zbigniew W. Raś
    • 1
    • 2
  • Agnieszka Dardzińska
    • 3
  • Osman Gürdal
    • 4
  1. 1.Dept. of Comp. Sci.Univ. of North CarolinaCharlotte
  2. 2.Institute of Comp. Sci.Polish Academy of SciencesWarsawPoland
  3. 3.Dept. of Math.Bialystok Technical Univ.BialystokPoland
  4. 4.Dept. of Comp. Sci. and Eng.Johnson C. Smith Univ.Charlotte

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