An XML-Based Database for Knowledge Discovery

  • Rosa Meo
  • Giuseppe Psaila
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4254)


Pattern Management Systems and Inductive Databases, are proposed as a new generation of general purpose databases with the aim to manage data mining patterns and work as knowledge bases in support to the deployment of the KDD process. One of the main problems to be solved is the integration between data and patterns and pattern maintenance when data update. Unfortunately, the heterogeneity of the patterns that represent the extracted knowledge and of the different conceptual tools used to find the patterns make difficult this integration in a unique framework.

In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, and present a model, named XDM (XML for Data Mining). We will show the basic features of the model, such as the storage in the same database of both data and patterns. To store patterns, we consider determinant for their interpretation the storage of the pattern derivation process which is described by the concept of statement, based on data mining operators. Some of the statements are automatically generated by the system while maintaining consistence between source and derived data. Furthermore, we show how the use of XML namespaces allows the effective coexistence of different data mining operators and provides extensibility to new operators. Finally, we show that with the use of XML-Schema we are able to define the schema, the state and the integrity constraints of an inductive database.


Association Rule Data Item Integrity Constraint Element Node Knowledge Discovery Process 
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.
    Alcamo, P., Domenichini, F., Turini, F.: An xml based environment in support of the overall kdd process. In: FQAS (2000)Google Scholar
  2. 2.
    Biron, P.V., Malhotra, A.: Xml schema part 2: Data types. Technical Report REC-xmlschema-2-20010502, World Wide Web Consortium (May 2001),
  3. 3.
    Braga, D., Campi, A., Ceri, S., Klemettinen, M., Lanzi, P.L.: Discovering interesting information in xml data with association rules. In: ACM SAC (2003)Google Scholar
  4. 4.
    Buchner, A.G., Baumgarten, M.: Data mining and xml: Current and future issues. In: Int. Conf. on Web Information Systems Engineering (2000)Google Scholar
  5. 5.
    Catania, B., Maddalena, M., Mazza, Bertino, E., Rizzi., S.: A framework for data mining pattern management. In: Proc. of ECML-PKDD 2004, Italy (September 2004)Google Scholar
  6. 6.
    DMG. The pmml language,
  7. 7.
    Edmonds, A.N.: Xmlminer, xmlrule and metarule white paper. Technical report, Scientio, Inc. (2002),
  8. 8.
    Imielinski, T., Mannila, H.: A database perspective on knowledge discovery. Communications of the ACM 39(11), 58–64 (1996)CrossRefGoogle Scholar
  9. 9.
    Meo, R., Psaila, G., Ceri, S.: An extension to SQL for mining association rules. Journal of Data Mining and Knowledge Discovery 2(2) (1998)Google Scholar
  10. 10.
    Psaila, G.: Enhancing the kdd process in the relational database mining framework by quantitative evaluation of association rules. In: Knowledge Discovery for Business Information Systems. Kluwer Academic Publishers, Dordrecht (2001)Google Scholar
  11. 11.
    Rizzi, S.: Uml-based conceptual modeling of pattern-bases. In: Proc. of PaRMA 2004 (2004)Google Scholar
  12. 12.
    Rizzi, S., Bertino, E., Catania, B., Golfarelli, M., Halkidi, M., Terrovitis, M., Vassiliadis, P., Vazirgiannis, M., Vrachnos, E.: Towards a logical model for patterns. In: Song, I.-Y., Liddle, S.W., Ling, T.-W., Scheuermann, P. (eds.) ER 2003. LNCS, vol. 2813, pp. 77–90. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  13. 13.
    Thompson, H.S., Beech, D., Maloney, M., Mendelsohn, N.: Xml schema part 1: Structures. Technical Report REC-xmlschema-1-20010502, World Wide Web Consortium (May 2001),

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rosa Meo
    • 1
  • Giuseppe Psaila
    • 2
  1. 1.Dipartimento di InformaticaUniversità di TorinoTorinoItaly
  2. 2.Facoltà di IngegneriaUniversità di BergamoDalmine (BG)Italy

Personalised recommendations