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基于SWRL的梨树病害领域本体隐含关系挖掘 被引量：1

Mining of Implicit Relations for Pear Diseases Domain Ontology Based on SWRL
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摘要 针对梨树病害领域本体的构建、推理及完善,本文提出了基于SWRL的梨树病害领域本体的构建方法,该方法包括确定梨树病害领域的核心概念集、添加概念的属性及概念之间的关系、添加概念的实例、表示领域本体四个步骤;此外,还设计了一系列SWRL规则,使用Jess推理引擎,建立了SWRL规则的推理机制,通过推理的方法实现了自动挖掘梨树病害领域本体的隐含关系,从而完善梨树病害领域本体。 Aiming to build, reason and perfect pear disease domain ontology, a build approach was proposed based on SWRL. The approach was consisted of confirming core concepts, the properties of added con- cepts and the relationships between concepts, the instances of added concepts and representing domain ontolo- gy. In addition, SWRL rules were designed, SWRL reasoning mechanism was established by Jess reasoning engine. Finally, implicit relationships were mined and diseases domain ontology was renewed by reasoning.
作者 孙倩 刘洪岩 王玥 姚胜男
机构地区 山东农业大学信息科学与工程学院 泰山职业技术学院信息中心
出处 《山东农业科学》 2015年第6期125-128,共4页 Shandong Agricultural Sciences
基金 国家农业信息化工程技术研究中心重点开放实验室开放课题(NERCITA-KFKT2013-001) 山东省2013年度农业重大应用技术创新课题
关键词 SWRL规则 梨树病害 领域本体 隐含关系 自动挖掘 SWRL rule Pear disease Domain ontology Implicit relation Automatic mining
分类号 S436.612.1 [农业科学—农业昆虫与害虫防治]
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参考文献9

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二级参考文献16

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  • 9Dumbill E. Berners-Lee and the Semantic Web Vision [ DB/OL]. (2000-12-06). [2010-10-16]. http://www, xml. corn/ pub/a/2000/12/xml2000/timbl, html.
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共引文献8

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二级引证文献6

山东农业科学
2015年 第6期

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