A Hybrid Scheme for Knowledge Representation

This study presents new methodology for knowledge representation called hybrid scheme for knowledge representation. The scheme is based on the integration of two different knowledge representation formats. The integration consists of the Rule-base and the Case-based formats using the Blackboard. This scheme uses both procedural and declarative knowledge representation formalisms through the application of relational database. So the rule base and case base formats have been converted into tables. The convert rule to table assigns the first attribute of table to be a conclusion of a rule and the reset of attributes as the conditions of a rule. Also assign the first attribute of table to be a cause of a case and the reset of attributes as the assertions of a case. In this study, all the algorithms, for creating, indexing and checking the availability of a rule and a case, are present. The scheme facilitates combination of forward and backward chaining reasoning, using many problems solving methodologies and different searching techniques. Therefore, the proposed scheme facilitates the common sense, deduction and analogical reasoning activities in the inference engine, because rule base provides the deduction, case base provides the analogical reasoning and the blackboard provides the common sense. This scheme will be used for developing shell expert system as new environment development for expert systems. The scheme makes the proposed Rule-Case-based shell expert system more flexible, efficient and more powerful for the development of the expert systems in future.