Viimeksi päivitetty 07.12.1998
Helsingin yliopisto
Rolf Nevanlinna -instituutti ja tietojenkäsittelytieteen laitos
Guest lecture
Jean-Francois Boulicaut
INSA Lyon, France
A KDD framework for database audit
Date Friday, 11 December 1998 Place
Rolf Nevanlinna Institute
Yliopistonkatu 5/Vuorikatu, 6th floorTime 11-12
Abstract
Understanding data semantics from real-life databases is considered following an audit perspective: it must help experts to analyse what properties actually hold in the data and support the comparison with desired properties. This is a typical problem of knowledge discovery in databases (KDD) and it is specified within the framework of Mannila and Toivonen where data mining consists in querying theories e.g., the theories of approximate inclusion dependencies. This formalization enables us to identify some important subtasks to support database audit, introducing the use of the inductive database framework. Finally, we consider the DREAM relational database reverse engineering method and DREAM heuristics are revisited within this new setting.
Welcome!
Hannu Toivonen