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Journal Articles Data Mining and Knowledge Discovery Year : 2012

An Inductive Database System Based on Virtual Mining Views

Toon Calders
  • Function : Author
Elisa Fromont
Bart Goethals
  • Function : Author
  • PersonId : 859234
Adriana Prado
  • Function : Author
  • PersonId : 858233
Céline Robardet


Inductive databases integrate database querying with database mining. In this article, we present an inductive database system that does not rely on a new data mining query language, but on plain SQL. We propose an intuitive and elegant framework based on virtual mining views, which are relational tables that virtually contain the complete output of data mining algorithms executed over a given data table. We show that several types of patterns and models that are implicitly present in the data, such as itemsets, association rules, and decision trees, can be represented and queried with SQL using a unifying framework. As a proof of concept, we illustrate a complete data mining scenario with SQL queries over the mining views, which is executed in our system.
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Dates and versions

hal-00599315 , version 1 (09-06-2011)
hal-00599315 , version 2 (14-06-2011)



Hendrik Blockeel, Toon Calders, Elisa Fromont, Bart Goethals, Adriana Prado, et al.. An Inductive Database System Based on Virtual Mining Views. Data Mining and Knowledge Discovery, 2012, 24 (1), pp.265-287. ⟨10.1007/s10618-011-0229-7⟩. ⟨hal-00599315v2⟩
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