A key challenge of complicated decision problem understanding is to make the information of decision problem

i.e.domain

goal

status and structure

readable and understandable for decision support system.This paper introduces ontology to describe semantics

and then problem semantic relationship and semantic computation are presented.Based on the rule of keeping the understanding results unchanged

semantic iteration method is addressed in order to transform the decision problem semantics

which cannot be analyzed through ontology

into fully understandable problem semantic.Further

semantic refining method is presented so that each complicated decision problem space can be refined into a most optimized closed problem space with a minimum complexity

which can be calculated from two facets:structure complexity and content complexity of problem space.Experiments show that the method of complicated decision problem semantic analysis is effective and feasible.