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Visual Mining of Association Rules

  • Dario Bruzzese
  • Cristina Davino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4404)

Abstract

Association Rules are one of the most widespread data mining tools because they can be easily mined, even from very huge database, and they provide valuable information for many application fields such as marketing, credit scoring, business, etc. The counterpart is that a massive effort is required (due to the large number of rules usually mined) in order to make actionable the retained knowledge. In this framework vizualization tools become essential to have a deep insight into the association structures and interactive features have to be exploited for highlighting the most relevant and meaningful rules.

Keywords

Data Mining Association Rule Mining Association Rule Multiple Correspondence Analysis Factorial Plane 
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 2008

Authors and Affiliations

  • Dario Bruzzese
    • 1
  • Cristina Davino
    • 2
  1. 1.Dipartimento di Scienze Mediche PreventiveUniversità di Napoli Federico IINapoliItaly
  2. 2.Dipartimento di Studi sullo Sviluppo EconomicoUniversità di MacerataMacerataItaly

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