Optimal Decomposition of Decision Table Systems Based on Bayesian Networks

It is shown that the decomposition method based on GDF (generalized decision function) is equivalent to that based on Bayesian networks in decision table systems; It is pointed out that the problem of information system decomposition is boiled down to those solving multiple sectioned Bayesian network (MSBN) and its d-separator set (d-sepset) corresponding to decision table systems; For the same Bayesian network (BN) owning various d-sepsets, various decomposition models exist. The relation between d-sepsets of MSBN and separator sets (sepsets) of linked junction forest (LJF) are put forward and proven, and it is shown that sepsets of LJF decide optimal d-sepsets of MSBN. Therefore the problem of decomposition of decision table systems is also to solve sepsets of LJF. Finally, feasibility of the method put forward is verified through an example.