OWL DL的形式化基础研究

W3C正在制定的OWL DL是一种面向语义Web的知识表示标记语言，具有较强的知识表达能力并适合大规模应用的推理效率，是语义Web领域对适合语义Web应用的知识表示标记语言进行研究的最新综合．在知识表示领域，为了对知识表达能力和推理效率做合适的折衷，进行了大量关于描述逻辑的研究，本文以描述逻辑作为OWL DL的形式化基础，详细分析了OWL DL和描述逻辑间的对应关系，用描述逻辑的语义解释了OWL DL的各个基本元素，从而可以将描述逻辑领域研究的大量成果应用到OWL DL上来，为进一步研究OWL DL的知识表示、推理等问题奠定了基础．     

语义Web中的知识表示语言

知识表示是语义web实现的基础,然而选择合适的知识表示语言是实现知识表示的第一步。本文针对三种有代表性的知识表示语言XML,RDF和OWL,从不同角度分析了三种知识表示语言的优点以及不足之处,并分析了语义web中本体知识表示语言将来的发展方向。     

基于OWL的电厂设备故障特征的知识表示

为了对电力行业复杂的故障信息进行有效的知识管理,本文将本体论方法引入到设备故障信息的知识表示中。利用OWL本体语言的知识表示特性,介绍了基于OWL的电厂设备故障特征知识表示的过程,为特定领域知识的公共一致表示提供了新的思路,本研究结果不仅可以促进电力行业知识的共享和重用,还方便了电力行业内部以及企业间知识管理和信息交换。     

基于OWL的自然灾害领域应急响应知识表示方法

利用语义网中本体和OWL(Ontology Web Language,即网络本体语言)等相关技术,通过一阶谓词逻辑及产生式知识表示方法具体描述地震灾害应急响应,为实现自然灾害领域应急响应的知识表示和共享提供一种参考。     

基于OWL本体的语义Web知识表示

语义Web是对当前Web的一种扩充,它的发展正逐渐将Internet变成一个巨大的全球化的知识库,利用本体进行知识表示是实现知识管理、体现语义Web价值的一种有效途径.本文在研究OWL本体进行知识表示的机制后,阐述形式化表示及语义说明方法,并结合实例说明知识的表示.     

基于描述逻辑的电机故障诊断知识表示与推理

针对传统电机故障诊断专家系统中知识表示方法的不足,提出一种基于描述逻辑的电机故障诊断领域知识描述方法,并在此基础上对所构建的电机故障知识库进行了逻辑检错推理.通过对电机故障诊断领域知识进行表示和推理,可以有效地表示电机故障知识之间的关系,检测知识逻辑体系错误.在实验过程中,利用本体编辑工具Protégé采用OWL语言对其进行了实现,并通过TABLEAU算法实现了逻辑检错推理.     

基于本体的设备维护知识表示研究*

为满足设备维护领域知识数字化表示的需求,根据设备维护领域知识的特点,将本体引入到该领域的知识表示中。通过对设备维护资源构成的分析,以设备维护知识中维修经验知识表示为例,分析其概念和属性关联关系,设计了维护案例本体表示方法。采用OWL对维护案例本体进行统一的形式化描述和表示,较好地解决了维修经验知识的共享与重用难题。研究提出的维修经验知识表示方法已在某大机组群监测系统中得到成功应用。     

基于本体论的应急系统知识表示的研究

论文在对知识表示及国内外有关本体库研究的基础上,提出将知识表示方法中的框架与谓词逻辑相结合,作为本体知识的一种描述方法,去定义国防动员应急决策支持系统中通信内容的共享本体,给出基于OWL+RDF+XML的形式化描述。并利用本体对知识进行领域分类,同时对决策者的查询信息进行规范。     

MAS中基于Ontology的知识表示与推理研究

采用基于Ontology的知识表示方法,解决多Agent的知识表示和共享问题,实现知识的自动推理和获取,实现多Agent之间语义理解,体现Agent的智能特征.在多Agent原型旅游系统中,采用OWL描述Ontology定义相关领域的知识表示与推理,为Agent之间的学习、协商,进一步交互通信打下基础.     

语义网知识表示的评价标准

基于Web具有的一些特征以及应用于语义网的知识表示语言，比较了语义网中知识表示和传统的知识表示的不同，提出了语义网知识表示的评价标准，并结合标准评价了现有的知识表示语言。     

基于语义Web的常用软件领域知识发现系统研究

当前,在语义Web中,基于OWL的知识表示、知识推理成为了研究和应用的热点.给出了常用软件本体的设计方法、规则定义和谓词扩展,并介绍了常用软件领域知识发现系统的总体模型.     

基于OWL的成语典故本体构建研究

本体是共享概念模型的明确的形式化规范说明,作为知识表示和知识共享的一种方法,本体是目前信息处理领域研究的热点。基于本体论的思想,利用骨架法构建了成语典故本体,并用OWL语言对成语典故本体进行形式化描述。详细介绍了成语典故本体的目的和使用范围、知识采集提炼及OWL描述,OWL描述分别从类、子类、属性、个体及关系几个方面进行了详细分析,为成语典故相关知识的查询奠定基础。通过成语典故本体的构建可有效对成语典故进行智能检索,是本体技术在中国传统文化中应用的尝试。     

Automatically generating assembly tolerance types with an ontology-based approach

In most cases, designers have to manually specify both assembly tolerance types and values when they design a mechanical product. Different designers will possibly specify different assembly tolerance types and values for the same nominal geometry. Furthermore, assembly tolerance specification design of a complex product is a highly collaborative process, in which semantic interoperability issues significantly arise. These situations will cause the uncertainty in assembly tolerance specification design and finally affect the quality of the product. In order to reduce the uncertainty and to support the semantic interoperability in assembly tolerance specification design, an ontology-based approach for automatically generating assembly tolerance types is proposed. First of all, an extended assembly tolerance representation model is constructed by introducing a spatial relation layer. The constructed model is hierarchically organized and consists of part layer, assembly feature surface layer, and spatial relation layer. All these layers are defined with Web Ontology Language (OWL) assertions. Next, a meta-ontology for assembly tolerance representations is constructed. With this meta-ontology, the domain-specific assembly tolerance representation knowledge can be derived by reusing or inheriting the classes or properties. Based on this, assembly tolerance representation knowledge is formalized using OWL. As a result, assembly tolerance representation knowledge has well-defined semantics due to the logic-based semantics of OWL, making it possible to automatically detect inconsistencies of assembly tolerance representation knowledge bases. The mapping relations between spatial relations and assembly tolerance types are represented in Semantic Web Rule Language (SWRL). Furthermore, actual generation processes of assembly tolerance types are carried out using Java Expert System Shell (JESS) by mapping OWL-based structure knowledge and SWRL-based constraint knowledge into JESS facts and JESS rules, respectively. Based on this, an approach for automatically generating assembly tolerance types is proposed. Finally, the effectiveness of the proposed approach is demonstrated by a practical example.     

Translating the Foundational Model of Anatomy into OWL

The Foundational Model of Anatomy (FMA) represents the result of manual and disciplined modeling of the structural organization of the human body. It is a tremendous resource in bioinformatics that facilitates sharing of information among applications that use anatomy knowledge. The FMA was developed in Protégé and the Protégé frames language is the canonical representation language for the FMA. We present a translation of the original Protégé frame representation of the FMA into OWL. Our effort is complementary to the earlier efforts to represent FMA in OWL and is focused on two main goals: (1) representing only the information that is explicitly present in the frames representation of the FMA or that can be directly inferred from the semantics of Protégé frames; (2) representing all the information that is present in the frames representation of the FMA, thus producing an OWL representation for the complete FMA. Our complete representation of the FMA in OWL consists of two components: an OWL DL component that contains the FMA constructs that are compatible with OWL DL; and an OWL Full component that imports the OWL DL component and adds the FMA constructs that OWL DL does not allow.     

DL-Learner—A framework for inductive learning on the Semantic Web

In this system paper, we describe the DL-Learner framework, which supports supervised machine learning using OWL and RDF for background knowledge representation. It can be beneficial in various data and schema analysis tasks with applications in different standard machine learning scenarios, e.g. in the life sciences, as well as Semantic Web specific applications such as ontology learning and enrichment. Since its creation in 2007, it has become the main OWL and RDF-based software framework for supervised structured machine learning and includes several algorithm implementations, usage examples and has applications building on top of the framework. The article gives an overview of the framework with a focus on algorithms and use cases.     

Development of a product configuration system with an ontology-based approach

Product configuration is a crucial means to implement the mass customization paradigm by assembling a set of customizable components to satisfy both customers’ needs and technical constraints. With the aim of enabling efficient and effective development of product configuration systems by reusing configuration knowledge, an ontology-based approach to modeling product configuration knowledge is presented in this paper. The ontology-based product configuration models are hierarchically organized. At the lower level, a configuration meta-model is defined. Based on this meta-model, domain-specific configuration knowledge can be derived by reusing or inheriting the classes or relations in the meta-model. Configuration models are formalized using OWL (Ontology Web Language), an ontology representation language developed by W3C. As a result, configuration models have well-defined semantics due to the logic semantics of OWL, making it possible to automatically detect inconsistencies of configuration knowledge bases. Furthermore, configuration constraints are represented in SWRL, a rule language based on OWL. Finally, actual configuration processes are carried out using JESS, a rule engine for the Java platform, by mapping OWL-based configuration facts and SWRL-based configuration constraints into JESS facts and JESS rules, respectively. The proposed methodology is illustrated with an example for configuring the ranger drilling machine.     

本体在产品知识表达中的应用研究

随着全球化竞争的日趋激烈,当代企业必须更加灵活、有效地生产用户所需的产品,而在产品设计中,缺乏对产品功能设计的描述,这就限制了产品的知识表达、传播、共享。文中从产品知识表达存在的问题出发,提出了基于本体的产品知识表达四层模型,即结构层—行为层—基本功能层—元功能层,给出了各层本体的表示模式。最后以洗衣机为例,给出它在四层模型中的表示和OWL描述。结果证明把本体引入产品知识表达中是合理的,四层模型中各层知识表达模式的相互补充,更加完善了产品的知识表达。