A SMILE web-based interface for learning the causal structure and performing a diagnosis of a Bayesian network

Nipat Jongsawat, Wichian Premchaiswadi
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
Bayesian networks (BNs) are probabilistic graphical models that are widely used for building diagnosis-and decision-support expert systems. The construction of BNs with the help of human experts is a difficult and time consuming task, which is prone to errors and omissions especially when the problems are very complicated. Learning the structure of a Bayesian network model and causal relations from a dataset or database is important for large BNs analysis. This paper focuses on using a SMILE
more » ... -based interface for building the structure of BN models from a dataset by using different structural learning algorithms. In addition to building the structure of BN models, a SMILE web-based interface also provides the feature set of Bayesian diagnosis for the user. The web application uses a novel user-friendly interface which intertwines the steps in the data analysis with brief support instructions to the Bayesian approach adopted. A SMILE web-based interface has been developed based on SMILE (Structural Modeling, Interface, and Learning Engine), SMILEarn, and SMILE.NET wrapper. Keywords-Bayesian network, Bayesian diagnosis, decisionsupport expert systems, update belief, SMILE, SMILEarn, SMILE.NET wrapper, SMILE web-based interface I.
doi:10.1109/icsmc.2009.5346198 dblp:conf/smc/JongsawatP09a fatcat:q5ncofq5n5crlgajgmh734wrhi