Ever since the seminal paper by Imielinski and Mannila [11], inductive databases have been a constant theme in the data mining literature. Operationally, such an inductive database is a database in which models and patterns are first class citizens.

In the extensive literature on inductive databases there is at least one consequence of this operational definition that is conspicuously missing. That is the question: if we have models and patterns in our inductive database, how does this help to discover other models and patterns? This question is the topic of this paper.


Data Mining Bayesian Network Association Rule Association Rule Mining Relational Algebra 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Arno Siebes
    • 1
  1. 1.Department of Computer ScienceUniversiteit UtrechtUtrechtThe Netherlands

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