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标题：AN ENGINEERING MODEL BASED ON ONTOLOGY AND PROBABILISTIC CALCULATION TO SUPPORT THE DIAGNOSIS
其他标题：AN ENGINEERING MODEL BASED ON ONTOLOGY AND PROBABILISTIC CALCULATION TO SUPPORT THE DIAGNOSIS
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作者：Luiz Fernando Lopes ; Alexandre Leopoldo Gonçalves ; José Leomar Todesco 等
期刊名称：Sistemas Gestão
印刷版ISSN：1980-5160
出版年度：2011
卷号：6
期号：3
页码：272-293
DOI：10.7177/sg.2011.V6.N3.A4
语种：Portuguese
出版社：Universidade Federal Fluminense
摘要：O diagnóstico, como tarefa intensiva em conhecimento, é um processo complexo uma vez que existe uma grande variedade de elementos e circunstâncias a serem considerados para uma tomada de decisão. Incertezas geradas pela subjetividade, imprecisão e/ou falta de informações atualizadas existem em quase todos os estágios e interferem quanto à segurança e eficácia no resultado. Os dados e informações úteis, quando coletados e tratados adequadamente, provenientes de diagnósticos realizados e que permanecem em estado latente (despercebidos / adormecidos), podem tornar-se uma valiosa fonte de conhecimento se associados à experiência e observação do profissional que os utiliza. Assim, o objetivo deste artigo é propor um modelo de Engenharia do Conhecimento que possibilita a geração de novos conhecimentos para apoiar o processo de diagnóstico. As metodologias, métodos e técnicas da Engenharia do Conhecimento, utilizados neste modelo para apoiar este processo, são: CommonKADS, Ontologia, Cálculo Probabilístico e Sistemas de Descoberta Baseados na Literatura. Através da integração entre esses elementos, o modelo proposto é aplicado em um exemplo didático, o qual possibilita que evidências sejam destacadas e analisadas através de pesquisa literária como possíveis novos conhecimentos. Após a confirmação de um novo conhecimento, o processo de inferência é atualizado. Conclui-se, portanto, que, através desta pesquisa, o modelo proposto atende os requisitos para a geração de novos conhecimentos e contribui para o aperfeiçoamento da tarefa de diagnóstico.↓The diagnosis, as knowledge-intensive task, is a complex process since there is a wide variety ofelements and circumstances to be considered for a decision-making. Uncertainty generated by the subjectivity,vagueness and/or lack of updated information exist in almost all stages and interfere for the safety and efficacyin the outcome. The data and useful information, when collected and treated appropriately, deriving fromdiagnosis accomplished and which remain latent (unobserved/asleep), can become a valuable source ofknowledge if associated with the experience and observation of the individual who uses them. The goal ofthis article is to propose a model of Knowledge Engineering that allows the creation of new knowledge tosupport the diagnosis process. The methods and techniques of Knowledge Engineering, used on this model tosupport the process are: CommonKADS, Ontology, Probabilistic Calculation and Discovery Systems Basedon Literature. Through the integration of these elements, the proposed model is applied to a didactic examplewhich allows evidence to be highlighted and analyzed through research literature as potential new knowledge.After the information of a new knowledge, the inference process is updated. It is concluded, therefore, thatthrough this research, the proposed model meets the requirements for the generation of new knowledge, andcontributes to the improvement of the diagnostic test.
其他摘要：The diagnosis, as knowledge-intensive task, is a complex process since there is a wide variety ofelements and circumstances to be considered for a decision-making. Uncertainty generated by the subjectivity,vagueness and/or lack of updated information exist in almost all stages and interfere for the safety and efficacyin the outcome. The data and useful information, when collected and treated appropriately, deriving fromdiagnosis accomplished and which remain latent (unobserved/asleep), can become a valuable source ofknowledge if associated with the experience and observation of the individual who uses them. The goal ofthis article is to propose a model of Knowledge Engineering that allows the creation of new knowledge tosupport the diagnosis process. The methods and techniques of Knowledge Engineering, used on this model tosupport the process are: CommonKADS, Ontology, Probabilistic Calculation and Discovery Systems Basedon Literature. Through the integration of these elements, the proposed model is applied to a didactic examplewhich allows evidence to be highlighted and analyzed through research literature as potential new knowledge.After the information of a new knowledge, the inference process is updated. It is concluded, therefore, thatthrough this research, the proposed model meets the requirements for the generation of new knowledge, andcontributes to the improvement of the diagnostic test.
关键词：Sistemas; Gestão; Ciência da Informação;Engenharia do Conhecimento. Sistemas Baseados em Conhecimento. Diagnóstico. Ontologia. Cálculo Probabilístico.;Gestão da Tecnologia; Sistemas de Informação;Knowledge Engineering; Knowledge Based Systems; Diagnosis; Ontology; Probabilistic Calculation
其他关键词：Knowledge Engineering; Knowledge Based Systems; Diagnosis; Ontology; Probabilistic Calculation