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How to secure a high quality knowledge base in a rulebased system with uncertainty

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Although the first rule-based systems were created as early as thirty years ago, this methodology of expert systems designing still proves to be useful. It becomes especially important in medical applications, while treating evidence given in an electronic format. Constructing the knowledge base of a rule-based system and, especially, of a system with uncertainty is a difficult task because of the size of this base as well as its heterogeneous character. The base consists of facts, ordinary rules and meta-rules, which differ from each other regarding both the syntax structure and the semantics. Having no tool to aid designing and maintaining the knowledge base of a rule-based system with uncertainty, we propose the algebra of rules with uncertainty which gives us theoretical foundations to build such a tool. Using the tool, it will be possible to indicate the facts and rules of a redundant character, as well as the pairs of facts and the pairs of rules which are contradictory to each other. The above tool is used in designing and maintaining the knowledge base of a system intended to prognosticate the effects of a medical treatment of the bronchial asthma disease.
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Rule languages and inference engines incorporate reasoning capabilities to Web information systems. This paper presents an approach for the specification and development of Web applications performing the usual functionalities of data management and incorporating a rule engine for reasoning capabilities. The proposed approach is based on the definition of a high-level representation of the semantics of rule-based applications through a formalism for conceptual modeling combining lightweight ontologies and production rules. These models are used as the source for a model-driven method that applies several transformations to conceptual models generating the rule-based Web application code in an automatic process. As a result, the rule-based Web application embeds a rule engine suitable for deducing information by applying an inference process. The structure of the information managed by the Web application is based on ontology classes, whereas the logical expressions applied in reasoning are obtained from production rules of the model. A rule-based Web application has been developed and evaluated using a supporting tool that implements the ideas presented in this paper.
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