The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of ...The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of expert system.The application mode of ontology and semantic technology on the process parameters recommendation are mainly investigated.Firstly,the content about ontology,semantic web rule language(SWRL)rules and the relative inference engine are introduced.Then,the inference method about process based on ontology technology and the SWRL rule is proposed.The construction method of process ontology base and the writing criterion of SWRL rule are described later.Finally,the results of inference are obtained.The mode raised could offer the reference to the construction of process knowledge base as well as the expert system's reusable process rule library.展开更多
Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The ...Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.展开更多
使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负...使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负担。针对这一缺陷提出了基于向下求精规则和相容谓词的候选频繁模式生成方法,同时定义了谓词数量约束,从而避免产生过多的非频繁模式和冗余模式。实验证明该方法可提高频繁模式生成的效率。展开更多
针对当前Web服务侧重于满足用户功能性需求,对用户隐私保护考虑不足的问题,提出了一种基于本体推理的保护用户隐私的方法。分析了隐私领域框架体系,构建了一个隐私领域本体。将Web服务中用户的隐私偏好转换成SWRL(semantic Web rule lan...针对当前Web服务侧重于满足用户功能性需求,对用户隐私保护考虑不足的问题,提出了一种基于本体推理的保护用户隐私的方法。分析了隐私领域框架体系,构建了一个隐私领域本体。将Web服务中用户的隐私偏好转换成SWRL(semantic Web rule language)规则,并利用推理引擎基于SWRL规则对隐私本体知识库进行推理,推导出隐私策略符合用户隐私偏好的Web服务。通过实验证明了该方法可以防止用户隐私信息的泄露,能够有效地保护用户隐私。展开更多
在综合分析信息检索系统现状的基础上,探讨目前信息检索系统存在的问题,深入研究基于本体的信息检索系统的关键技术,包括领域本体的建设方法、SWRL(Semantic Web Rule Language)推理规则、基于本体的查询预处理以及语义处理,并从本体概...在综合分析信息检索系统现状的基础上,探讨目前信息检索系统存在的问题,深入研究基于本体的信息检索系统的关键技术,包括领域本体的建设方法、SWRL(Semantic Web Rule Language)推理规则、基于本体的查询预处理以及语义处理,并从本体概念相似度和相关度的角度论述了基于本体的语义处理技术。通过这些研究,提出了使用OWL构建领域本体,结合查询预处理以及推理扩展规则SWRL的信息检索模型。展开更多
在快速发展的信息化时代,各领域数据增长飞快,但由于数据来源多、结构松散、关系复杂多样,数据共享存在一定的困难。本体的出现促进了各领域的信息共享,以军事领域为例,构建军事事件本体、武器装备本体和战场环境本体模型。然后建立属...在快速发展的信息化时代,各领域数据增长飞快,但由于数据来源多、结构松散、关系复杂多样,数据共享存在一定的困难。本体的出现促进了各领域的信息共享,以军事领域为例,构建军事事件本体、武器装备本体和战场环境本体模型。然后建立属性关系、时空关系和语义关系来表达领域信息关联关系,综合考虑军事领域多要素,清晰地表达军事事件、武器装备、战场环境之间的复杂关系;最后,将语义网规则语言(Semantic Web Rule Language,SWRL)特点与本体相结合,对本体进行语义推理,挖掘领域内存在的隐含关系,为实现各领域的信息共享和智能检索提供基础。展开更多
基金supported by the National Science Foundation of China(No.51575264)the Jiangsu Province Science Foundation for Excellent Youths under Grant BK20121011the Fundamental Research Funds for the Central Universities(No.NS2015050)
文摘The process inference cannot be achieved effectively by the traditional expert system,while the ontology and semantic technology could provide better solution to the knowledge acquisition and intelligent inference of expert system.The application mode of ontology and semantic technology on the process parameters recommendation are mainly investigated.Firstly,the content about ontology,semantic web rule language(SWRL)rules and the relative inference engine are introduced.Then,the inference method about process based on ontology technology and the SWRL rule is proposed.The construction method of process ontology base and the writing criterion of SWRL rule are described later.Finally,the results of inference are obtained.The mode raised could offer the reference to the construction of process knowledge base as well as the expert system's reusable process rule library.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A2C1011198).
文摘Alzheimer’s disease(AD)is a very complex disease that causes brain failure,then eventually,dementia ensues.It is a global health problem.99%of clinical trials have failed to limit the progression of this disease.The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms.Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction.In this regard,the need becomes more urgent for biomarker-based detection.A key issue in understanding AD is the need to solve complex and high-dimensional datasets and heterogeneous biomarkers,such as genetics,magnetic resonance imaging(MRI),cerebrospinal fluid(CSF),and cognitive scores.Establishing an interpretable reasoning system and performing interoperability that achieves in terms of a semantic model is potentially very useful.Thus,our aim in this work is to propose an interpretable approach to detect AD based on Alzheimer’s disease diagnosis ontology(ADDO)and the expression of semantic web rule language(SWRL).This work implements an ontology-based application that exploits three different machine learning models.These models are random forest(RF),JRip,and J48,which have been used along with the voting ensemble.ADNI dataset was used for this study.The proposed classifier’s result with the voting ensemble achieves a higher accuracy of 94.1%and precision of 94.3%.Our approach provides effective inference rules.Besides,it contributes to a real,accurate,and interpretable classifier model based on various AD biomarkers for inferring whether the subject is a normal cognitive(NC),significant memory concern(SMC),early mild cognitive impairment(EMCI),late mild cognitive impairment(LMCI),or AD.
文摘使用SWRL(Semantic Web Rule Language)描述的数据蕴含了更多的语义信息,SWRL数据集上的数据挖掘过程必须充分考虑数据的语义特征。已有的关于这种类型数据的候选频繁模式生成方法可能产生大量无意义的模式,加重了模式评价过程的计算负担。针对这一缺陷提出了基于向下求精规则和相容谓词的候选频繁模式生成方法,同时定义了谓词数量约束,从而避免产生过多的非频繁模式和冗余模式。实验证明该方法可提高频繁模式生成的效率。
文摘针对当前Web服务侧重于满足用户功能性需求,对用户隐私保护考虑不足的问题,提出了一种基于本体推理的保护用户隐私的方法。分析了隐私领域框架体系,构建了一个隐私领域本体。将Web服务中用户的隐私偏好转换成SWRL(semantic Web rule language)规则,并利用推理引擎基于SWRL规则对隐私本体知识库进行推理,推导出隐私策略符合用户隐私偏好的Web服务。通过实验证明了该方法可以防止用户隐私信息的泄露,能够有效地保护用户隐私。
文摘在综合分析信息检索系统现状的基础上,探讨目前信息检索系统存在的问题,深入研究基于本体的信息检索系统的关键技术,包括领域本体的建设方法、SWRL(Semantic Web Rule Language)推理规则、基于本体的查询预处理以及语义处理,并从本体概念相似度和相关度的角度论述了基于本体的语义处理技术。通过这些研究,提出了使用OWL构建领域本体,结合查询预处理以及推理扩展规则SWRL的信息检索模型。
文摘在快速发展的信息化时代,各领域数据增长飞快,但由于数据来源多、结构松散、关系复杂多样,数据共享存在一定的困难。本体的出现促进了各领域的信息共享,以军事领域为例,构建军事事件本体、武器装备本体和战场环境本体模型。然后建立属性关系、时空关系和语义关系来表达领域信息关联关系,综合考虑军事领域多要素,清晰地表达军事事件、武器装备、战场环境之间的复杂关系;最后,将语义网规则语言(Semantic Web Rule Language,SWRL)特点与本体相结合,对本体进行语义推理,挖掘领域内存在的隐含关系,为实现各领域的信息共享和智能检索提供基础。
