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Incorporating Evidence in Bayesian Networks with the Select Operator
Author(s) -
Cory J. Butz,
F. Fang
Publication year - 2005
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-25864-7
DOI - 10.1007/11424918_31
Subject(s) - computer science , bayesian network , operator (biology) , probabilistic logic , relational database , bayesian probability , knowledge base , expert system , artificial intelligence , data mining , theoretical computer science , machine learning , biochemistry , chemistry , repressor , transcription factor , gene
In this paper, we propose that the select operator in relational databases be adopted for incorporating evidence in Bayesian networks This approach does not involve the construction of new evidence potentials, nor the associated computational costs of multiplying the evidence potentials into the knowledge base The select operator also provides unified treatment of hard and soft evidence in Bayesian networks Finally, some query optimization rules, involving the select operator implemented in relational databases, can be directly incorporated into probabilistic expert systems.

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