Towards Mining Frequent Queries in Star Schemes

  • Tao-Yuan Jen
  • Dominique Laurent
  • Nicolas Spyratos
  • Oumar Sy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3933)


The problem of mining all frequent queries in a database is intractable, even if we consider conjunctive queries only. In this paper, we study this problem under reasonable restrictions on the database, namely: (i) the database scheme is a star scheme; (ii) the data in the database satisfies a set of functional dependencies and a set of referential constraints.

We note that star schemes are considered to be the most appropriate schemes for data warehouses, while functional dependencies and referential constraints are the most common constraints that one encounters in real databases. Our approach is based on the weak instance semantics of databases and considers the class of selection-projection queries over weak instances. In such a context, we show that frequent queries can be mined using level-wise algorithms such as Apriori.


Association Rule Functional Dependency Selection Condition Relation Scheme Dimension Table 
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

  • Tao-Yuan Jen
    • 1
  • Dominique Laurent
    • 1
  • Nicolas Spyratos
    • 2
  • Oumar Sy
    • 1
    • 3
  1. 1.LICP, Université de Cergy-PontoiseCergy-PontoiseFrance
  2. 2.LRIOrsayFrance
  3. 3.Université Gaston BergerSaint-LouisSenegal

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