Automated fuzzy-clustering for Doctus expert system

Zoltán Baracskai, Viktor Dörfler

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Our Knowledge-Based Expert System Shell 'Doctus'1 is capable of deduction also called rule-based reasoning and of induction, which is the symbolic version of reasoning by cases2 . If connected to databases or data warehouses the inductive reasoning of Doctus is also used for data mining. To handle numerical domains Doctus uses statistical clustering algorithm. We define the problem in three steps: how to perform a clustering, which is neither rigid nor sensitive to noise, benefiting from the properties of the application domain, reducing the complexity as much as possible, and supplying the decision maker with useful information enabling the possibility of interaction? In this paper we present the conception of Automated FuzzyClustering using triangular and trapezoidal Fuzzy-sets, which provides overlapping Fuzzy-set covering of the domain.
Original languageEnglish
Number of pages6
Publication statusPublished - 29 Aug 2003
EventInternational Conference on Computational Cybernetics - Siófok, Hungary
Duration: 29 Aug 200331 Aug 2003


ConferenceInternational Conference on Computational Cybernetics
Abbreviated titleICCC 2003
Internet address


  • Doctus
  • fuzzy logic
  • expert system
  • decision support systems


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