2018
DOI: 10.3844/jcssp.2018.680.698
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Prototyping Rule-Based Expert Systems with the Aid of Model Transformations

Abstract: The problem of improving efficiency of intelligence systems engineering remains a relevant topic of scientific research. One of the trends in this area is the use of the principles of cognitive (visual) modelling and design as well as approaches based on generative programming and model transformations. This paper aims to describe the implementation and application of model transformations for prototyping rule-based knowledge bases and expert systems. The implementation proposed uses the main principles of the… Show more

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Cited by 10 publications
(3 citation statements)
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“…The final phase generates source codes of a target knowledge base from a conceptual model obtained at the previous phase. The synthesis algorithm is based on the generalized method for transforming a conceptual model to a knowledge base presented in [37]. This method implies the application of metamodels and a domain-specific declarative language for describing correspondences between source elements of a conceptual model and target elements of a rule-based model.…”
Section: Synthesizing Rule-based Knowledge Basesmentioning
confidence: 99%
See 2 more Smart Citations
“…The final phase generates source codes of a target knowledge base from a conceptual model obtained at the previous phase. The synthesis algorithm is based on the generalized method for transforming a conceptual model to a knowledge base presented in [37]. This method implies the application of metamodels and a domain-specific declarative language for describing correspondences between source elements of a conceptual model and target elements of a rule-based model.…”
Section: Synthesizing Rule-based Knowledge Basesmentioning
confidence: 99%
“…Step 3: Modify the obtained rule-based model by using Rule Visual Modeling Language (RVML) [37] is a UML extension designed for rule-based engineering.…”
Section: Synthesizing Rule-based Knowledge Basesmentioning
confidence: 99%
See 1 more Smart Citation