Abstract
We have been proposing a framework Rough Non-deterministic Information Analysis (RNIA), which handles rough sets based concepts in not only Deterministic Information Systems (DISs) but also Non-deterministic Information Systems (NISs). We have recently developed some algorithms and software tools for rule generation from NISs. Obtained rules characterize the tendencies in NISs, and they are often applied to decision making. However, if the condition parts in such rules are not satisfied, obtained rules are not applied to decision making. In this case, we need to examine each data in NISs, directly. In this paper, we add a question-answering with criterion values to RNIA. This addition enhances the aspect of decision making in RNIA.KeywordsIncomplete InformationCondition PartApriori AlgorithmGranular ComputingReal ExecutionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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