OWL:一种用于语义网的描述逻辑

本体是语义网中的重要内容,它通过提供一个共享的、精确定义的术语源将语法扩展到语义.OWL是专门为Web设计的本体语言,它利用现有的Web标准(XML和RDF),添加了面向对象和基于框架的系统中常见的本体原语,具有强表达性的描述逻辑的严格形式化.OWL的逻辑基础是可以提供推理服务,既支持本体设计,又使得其在描述网络资源方面更接近于自动处理过程.     

基于本体和规则的扬弹机故障诊断研究

通过对OWL(Web Ontology Language,OWL)本体和SWRL规则语言进行研究,将基于本体和规则的知识表示和智能推理技术应用到舰船扬弹机的故障诊断中。构建了舰船扬弹机的OWL本体及相关的故障诊断SWRL(Semantic Web Rule Language,SWRC)规则,在此基础上开发出一个故障诊断的系统,并实现了诊断推理过程。该系统能帮助设备维护员快速定位故障发生原因,并提供可选用排除故障的基本措施。     

Developing manufacturing ontologies for knowledge reuse in distributed manufacturing environment

The use of ontologies for knowledge sharing and distributed collaboration has been widely recognised in the knowledge modelling community, but the lack of a systematic and constructive methodology for developing manufacturing ontologies has impeded their wide usage for knowledge reuse in distributed manufacturing environments. This paper presents a constructive, two-level knowledge modelling approach to systematically develop manufacturing ontologies using both software engineering and Semantic Web paradigms. The UML/OCL (Unified Modeling Language/Object Constraint Language)-based object modelling is used first to serve as a graphical and structured basis for conceptual communication between domain experts and knowledge engineers. The OWL/SWRL (Web Ontology Language/Semantic Web Rule Language)-based ontology modelling then extends the UML/OCL-based object models with added semantics using a progressive, semantics-oriented knowledge acquisition method. An illustrative example for manufacturing ontology development in the manufacturing industry for producing electronic connectors is used to demonstrate the practicality of the proposed approach.     

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.     

注射模改模知识应用本体的建模方法

分析了注射模改模知识的特点和本体表示知识的方法,提出了构建应用本体的新模式,重点讨论了构造应用本体的克隆、合并、遗传,新建等4种建模方法,利用Protege软件建立了注射模改模知识应用本体,并转换为Web OWL语言。实践证明该方法能够较好地表示注射模改模知识。     

基于语义Web技术的油（气）井监视用例的介绍与评价

对于与监测、监控和优化相关的大量的工作流程而言,事件信息是非常有价值的。一个事件的主要属性,包括其类型、发生时间、受事件影响的实体、事件发生前、中、后实体的状态,以及该事件与其他事件之间的关系。这里总结了使用语义Web技术开发油（气）井监视软件的经验,通过探讨语义Web技术的实用性和适用性,建立了事件建模与分析系统,在事件建模的基础上,用语义网规则语言（SWRL）来表示有关事件关系的知识,事件之间的关系可使用现成的规则引擎自动推断得到。研究的目的是通过开发语义Web技术这一具有前景的方法,为数据处理领域事件建立具有可扩展性和可维护性的系统。     

ComR: a combined OWL reasoner for ontology classification

Ontology classification, the problem of computing the subsumption hierarchies for classes (atomic concepts), is a core reasoning service provided by Web Ontology Language (OWL) reasoners. Although general-purpose OWL 2 reasoners employ sophisticated optimizations for classification, they are still not efficient owing to the high complexity of tableau algorithms for expressive ontologies. Profile-specific OWL 2 EL reasoners are efficient; however, they become incomplete even if the ontology contains only a small number of axioms that are outside the OWL 2 EL fragment. In this paper, we present a technique that combines an OWL 2 EL reasoner with an OWL 2 reasoner for ontology classification of expressive SROIQ. To optimize the workload, we propose a task decomposition strategy for identifying the minimal non-EL subontology that contains only necessary axioms to ensure completeness. During the ontology classification, the bulk of the workload is delegated to an efficient OWL 2 EL reasoner and only the minimal non- EL subontology is handled by a less efficient OWL 2 reasoner. The proposed approach is implemented in a prototype ComR and experimental results show that our approach offers a substantial speedup in ontology classification. For the wellknown ontology NCI, the classification time is reduced by 96.9% (resp. 83.7%) compared against the standard reasoner Pellet (resp. the modular reasoner MORe).     

语义网的体系结构与服务功能

近年来,语义网的研究引起了计算机业界的广泛关注。本文作者认为对语义网的研究成果将对现今互联网上的信息发布,信息处理以及信息服务产生巨大的变革。基于此原因,本文对语义网产生的背景、基本概念、体系结构进行介绍与分析,最后讨论了语义网能够提供给我们全新的网络服务。     

基于网络本体语言的三维计算机辅助设计主模型相似性计算方法

为了提高三维计算机辅助设计(CAD)模型重用效率,针对当前三维模型检索系统中语义表达不足问题,提出了一种基于网络本体语言(OWL)表示模型语义的相似性计算方法。首先,将三维CAD产品主模型转化成以概念属性特征为基础语义对象的结构化表示模型;然后,从OWL表示模型中提取用于评价两个模型相似性的特征语义信息,构建可量化的相似元集,借助子图同构思想和Tversky算法给出了一种加权相似性计算方法;最后,通过实例验证了所提方法的有效性和可行性。实验的定量评价结果表明,该评价基准从对象本身转为两个对象特性的语义描述,能够客观反映两对比模型的相似程度。