Automatic rule acquisition through ontology from the web : XRML approach = 온톨로지를 활용한 웹으로부터의 자동화된 규칙습득 : XRML 접근방식 XRML approach

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As research on the Semantic Web actively progresses, a more intelligent Web environment is expected for the next generation in various domains including rule based systems and intelligent agents. However, rule acquisition is still a bottleneck in the utilization of the rule based systems. To extract rules from Web pages and maintain consistency between them, the framework of XRML (eXtensible Rule Markup Language) has been developed. XRML allows the identification of rules from Web pages and generates the identified rules automatically. The important feature of XRML is that rule identification provides a significant level of automation in rule generation. However, the knowledge engineer’s burden is still high because rule identification requires considerable manual work. In order to reduce the knowledge engineer’s burden in rule acquisition, we have suggested a rule identification methodology through ontology based on the XRML approach. As the first step of our approach, we showed the role of ontology in rule acquisition and described various issues on using ontology such as the necessity of a specified ontology for rule acquisition, the degree of ontology expression for rules, the method of applying ontology in rule acquisition, and the management of ontology scope. Also we designed an ontology for rule acquisition named OntoRule because the ontology can substitute for the knowledge engineer’s experience based on these issues. For the second step, we proposed a rule acquisition procedure that automatically identifies rule components such as variables and values from the Web page by using OntoRule. Moreover, we proposed the best-first search algorithm that automatically composes rules from the identified variables and values through OntoRule. We also described various issues and further research topics on using OntoRule and the best-first search for rule acquisition. The knowledge engineer completes rule acquisition by adding those missing components and corre...
Kim, Young-GulresearcherLee, Jae-Kyuresearcher김영걸researcher이재규researcher
한국과학기술원 : 경영공학전공,
Issue Date
260102/325007  / 000995147

학위논문(박사) - 한국과학기술원 : 경영공학전공, 2006.8, [ viii, 132 p. ]


Semantic Web; Rule Acquisition; Best First Search; 확장형규칙표식언어; 온톨로지; 시맨틱 웹; 규칙습득; 최적우선탐색; XRML; Ontology

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