A Methodological Approach for the Effective Modeling of Bayesian Networks

  • Martin Atzmueller
  • Florian Lemmerich
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5243)

Abstract

Modeling Bayesian networks manually is often a tedious task. This paper presents a methodological view onto the effective modeling of Bayesian networks. It features intuitive techniques that are especially suited for inexperienced users: We propose a process model for the modeling task, and discuss strategies for acquiring the network structure. Furthermore, we describe techniques for a simplified construction of the conditional probability tables using constraints and a novel extension of the Ranked-Nodes approach. The effectiveness and benefit of the presented approach is demonstrated by three case studies.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Martin Atzmueller
    • 1
  • Florian Lemmerich
    • 1
  1. 1.Department of Computer Science VI Am HublandUniversity of WürzburgWürzburgGermany

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