TY - GEN

T1 - Construction of a Bayesian network as an extension of propositional logic

AU - Enomoto, Takuto

AU - Kimura, Masaomi

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Association rule mining

KW - Bayesian network

KW - Propositional logic

UR - http://www.scopus.com/inward/record.url?scp=84960883615&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960883615&partnerID=8YFLogxK

U2 - 10.5220/0005595102110217

DO - 10.5220/0005595102110217

M3 - Conference contribution

AN - SCOPUS:84960883615

T3 - IC3K 2015 - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

SP - 211

EP - 217

BT - KDIR

A2 - Fred, Ana

A2 - Dietz, Jan

A2 - Aveiro, David

A2 - Liu, Kecheng

A2 - Filipe, Joaquim

A2 - Filipe, Joaquim

PB - SciTePress

T2 - 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015

Y2 - 12 November 2015 through 14 November 2015

ER -