A deductive query processor for statistical databases

  • Carla Basili
  • Leonardo Meo-Evoli
Conference paper


Statistical data are complex data structures, which traditional data models are not sufficient to represent. Such a complexity transfers directly to statistical data manipulations, imposing on the user a great effort in specifying detailed algorithms. An high level language should be desirable, by which the user can specify only the starting data and the logical structure of the result. Such conceptual interaction requires an automatic mapping, transforming the high level operator into a number of elementary operations.

This paper describes a statistical data model suitable to represent the complexity of statistical data structures and suitable to be processed by high level operators.

This is followed by the description of a knowledge-based mechanism to deduce the elementary operations underlying an high level operator.

Finally, a deductive query processor, StEM, is shown, which provides transparency of complex data manipulations, using both the above data model and deduction mechanism.


Query Processing Statistical Database Kernel Module High Level Language Operative Link 
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/Wien 1992

Authors and Affiliations

  • Carla Basili
    • 1
  • Leonardo Meo-Evoli
    • 1
  1. 1.Istituto di Studi sulla Ricerca e sulla Documentazione ScientificaConsiglio Nazionale delle Ricerche (CNR)RomaItaly

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