Personal knowledge base designer: Software for expert systems prototyping
In most cases, the complexity of expert systems engineering depends on the complexity of knowledge base engineering. This process includes formalization and programming tasks. In this connection, the use of visual programming, model transformation and code generation principles are relevant. We pres...
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doaj-179d2b79fc6848b2bc8a991ffcafeb822020-11-25T02:52:03ZengElsevierSoftwareX2352-71102020-01-0111Personal knowledge base designer: Software for expert systems prototypingAleksandr Yu. Yurin0Nikita O. Dorodnykh1Corresponding author.; Matrosov Institute for System Dynamics and Control Theory, Siberian Branch of the Russian Academy of Sciences, 134 Lermontov St., Irkutsk, 664033, RussiaMatrosov Institute for System Dynamics and Control Theory, Siberian Branch of the Russian Academy of Sciences, 134 Lermontov St., Irkutsk, 664033, RussiaIn most cases, the complexity of expert systems engineering depends on the complexity of knowledge base engineering. This process includes formalization and programming tasks. In this connection, the use of visual programming, model transformation and code generation principles are relevant. We present a new software with similar properties. Our software provides the use of a domain-specific notation for rule modeling, namely, Rule Visual Modeling Language (RVML); wizards for creating and editing knowledge base elements; conceptual models and canonical spreadsheet tables as main sources of domain knowledge. The core of the new software is a unified model for representing and editing knowledge in the form of logical rules, as well as its interpretation using the built-in rule engine. This enables the use of conceptual models in the form of UML class diagrams, concept maps, mind maps, Ishikawa diagrams and others as a source of information, and also helps involve non-programming users in the process of knowledge base engineering and to minimize coding errors. Our empirical results demonstrate the ability to use the proposed software for prototyping rule-based knowledge bases by transforming different conceptual models. Two case studies are also presented.http://www.sciencedirect.com/science/article/pii/S2352711019303334Visual modelingKnowledge baseRulesRVMLConceptual models |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aleksandr Yu. Yurin Nikita O. Dorodnykh |
spellingShingle |
Aleksandr Yu. Yurin Nikita O. Dorodnykh Personal knowledge base designer: Software for expert systems prototyping SoftwareX Visual modeling Knowledge base Rules RVML Conceptual models |
author_facet |
Aleksandr Yu. Yurin Nikita O. Dorodnykh |
author_sort |
Aleksandr Yu. Yurin |
title |
Personal knowledge base designer: Software for expert systems prototyping |
title_short |
Personal knowledge base designer: Software for expert systems prototyping |
title_full |
Personal knowledge base designer: Software for expert systems prototyping |
title_fullStr |
Personal knowledge base designer: Software for expert systems prototyping |
title_full_unstemmed |
Personal knowledge base designer: Software for expert systems prototyping |
title_sort |
personal knowledge base designer: software for expert systems prototyping |
publisher |
Elsevier |
series |
SoftwareX |
issn |
2352-7110 |
publishDate |
2020-01-01 |
description |
In most cases, the complexity of expert systems engineering depends on the complexity of knowledge base engineering. This process includes formalization and programming tasks. In this connection, the use of visual programming, model transformation and code generation principles are relevant. We present a new software with similar properties. Our software provides the use of a domain-specific notation for rule modeling, namely, Rule Visual Modeling Language (RVML); wizards for creating and editing knowledge base elements; conceptual models and canonical spreadsheet tables as main sources of domain knowledge. The core of the new software is a unified model for representing and editing knowledge in the form of logical rules, as well as its interpretation using the built-in rule engine. This enables the use of conceptual models in the form of UML class diagrams, concept maps, mind maps, Ishikawa diagrams and others as a source of information, and also helps involve non-programming users in the process of knowledge base engineering and to minimize coding errors. Our empirical results demonstrate the ability to use the proposed software for prototyping rule-based knowledge bases by transforming different conceptual models. Two case studies are also presented. |
topic |
Visual modeling Knowledge base Rules RVML Conceptual models |
url |
http://www.sciencedirect.com/science/article/pii/S2352711019303334 |
work_keys_str_mv |
AT aleksandryuyurin personalknowledgebasedesignersoftwareforexpertsystemsprototyping AT nikitaodorodnykh personalknowledgebasedesignersoftwareforexpertsystemsprototyping |
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