Construction of a Bayesian network as an extension of propositional logic

Takuto Enomoto, Masaomi Kimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A Bayesian network is a probabilistic graphical model. Many conventional methods have been proposed for its construction. However, these methods often result in an incorrect Bayesian network structure. In this study, to correctly construct a Bayesian network, we extend the concept of propositional logic. We propose a methodology for constructing a Bayesian network with causal relationships that are extracted only if the antecedent states are true. In order to determine the logic to be used in constructing the Bayesian network, we propose the use of association rule mining such as the Apriori algorithm. We evaluate the proposed method by comparing its result with that of traditional method, such as Bayesian Dirichlet equivalent uniform (BDeu) score evaluation with a hill climbing algorithm, that shows that our method generates a network with more necessary arcs than that generated by the traditional method.

Original languageEnglish
Title of host publicationKDIR
EditorsAna Fred, Jan Dietz, David Aveiro, Kecheng Liu, Joaquim Filipe, Joaquim Filipe
PublisherSciTePress
Pages211-217
Number of pages7
ISBN (Electronic)9789897581588
DOIs
Publication statusPublished - 2015
Event7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015 - Lisbon, Portugal
Duration: 2015 Nov 122015 Nov 14

Publication series

NameIC3K 2015 - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Volume1

Other

Other7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015
CountryPortugal
CityLisbon
Period15/11/1215/11/14

Keywords

  • Association rule mining
  • Bayesian network
  • Propositional logic

ASJC Scopus subject areas

  • Software

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  • Cite this

    Enomoto, T., & Kimura, M. (2015). Construction of a Bayesian network as an extension of propositional logic. In A. Fred, J. Dietz, D. Aveiro, K. Liu, J. Filipe, & J. Filipe (Eds.), KDIR (pp. 211-217). (IC3K 2015 - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management; Vol. 1). SciTePress. https://doi.org/10.5220/0005595102110217