基于语义网规则语言的推理机制框架设计

分析了本体描述语言OWL DL在表达能力上局限于描述逻辑的缺陷以及语义网规则语言(semantic web rule language,SWRL)的特点,在已有时本体和规则结合推理的研究基础上,提出了一个基于SWRL的推理机制框架.该框架在OWL本体中引入了规则的表示,弥补了OWLDL在推理机制上的不足,经该框架推导出的新本体在原本体的基础上增加了概念间的语义关联,将隐性知识显示化,完善了本体知识库的内容.在语义Web领域,该框架的应用能够提高本体知识的利用率.     

基于本体共享的专家系统模型

提出了基于本体共享的专家系统模型,该模型充分利用了本体的共享特性.通过利用本体对知识进行表示,用SWRL编写规则,可以有效的表示知识之间的关系,有利于知识的共享和重用.     

基于SWRL本体推理研究

随着语义Web的兴起,本体技术已成为计算机学科中的一个研究热点。在分析本体、Web本体语言OWL和语义网规则描述语言SWRL的概念和特点的基础上,利用MPEG-7标准中的视觉描述子来描述图像的特征,采用本体建立图像的语义特征,将SWRL引入图像情感识别领域,利用SWRL构建推理规则。通过建立图像的本体信息和推理规则,并用规则推理出本体中隐含的信息,实现图像情感识别,使计算机具有一定的情感推理能力。     

基于本体的图像情感语义识别研究

抽取图像颜色、形状、纹理特征,通过本体映射,建立本体表示的图像情感特征库。以中国情感图片系统作为训练样本,挖掘图像特征与情感之间的关联关系,并通过语义网规则语言SWRL（Semantic Web Rule Language）表示关联规则,建立情感映射规则库。情感推理引擎使用情感映射规则对图像特征进行推理,达到识别图像情感语义的目的。     

故障树领域本体及SWRL规则的构建方法研究

故障树(Fault Tree,FT)被广泛应用于系统故障的快速定位,但其因缺乏精确的语义信息而存在重复构建问题。将本体引入到故障树领域中,并对如何构建故障树本体及相应的SWRL规则进行了研究:首先采用本体描述语言 (Web Ontology Language,OWL)对故障树中的概念及概念之间的关系进行知识表示,构建了一个可共享、可重用、可扩展的故障树领域本体;然后将故障树中事件之间的逻辑关系转化成语义 Web 规则语言 (Semantic Web Rule Language,SWRL);最后将构建的故障树领域本体和SWRL规则放入JESS推理机中进行推理,产生新的知识,用于系统故障的快速定位。实验证明,使用所提出的方法能在解决故障树重复构建问题的同时,不对系统故障的快速定位产生影响。     

电子目录的SWRL规则研究

随着电子商务网站和在线商品数量不断增加,电子目录技术变得越来越重要。现有电子目录及标准只是产品分级概念和属性的结合,不能进行基于规则推理的智能化服务,使用SWRL编写电子目录本体的产品关联规则,可以更好地提供基于规则推理的电子目录服务。主要在电子目录标准、本体论和语义Web研究基础上,利用SWRL语言的逻辑表达能力,来构造与研究电子目录本体的SWRL规则,并对产品配置规则,规则推理做出探讨。     

基于本体增强语义规则的复杂配电网安全作业控制研究与实现

提出一种基于网络本体语言(OWL)和语义网规则语言(SWRL)的复杂配电网安全作业控制方法。系统基于网络本体语言建立一个可共享、可重用、可扩展的配网安全作业领域本体;将配电网安全防误规则转换成由语义网规则语言表达的推理规则;整合SWRL推理规则与Racer推理机进行推理。系统将电力安全防误规则转换成SWRL形成面向电力的语义网规则语言e-SWRL。实验验证了基于OWL和SWRL的电力安全防误推理方法的有效性与正确性。     

基于SWRL规则与本体相似度的语义检索模型研究

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。     

基于本体的机场跑道侵入智能违规诊断研究*

为保证机场场面运行安全,从知识建模角度出发,提出智能信息处理方法诊断违规项目,使用SWRL、领域本体等技术构建跑道侵入违规诊断系统的本体模型。研究了将跑道侵入案例用语义规则形式化表示的方法,构建推理规则得出违规项目和硬件预防措施。结果表明,提出的方法较传统方法,结合本体和SWRL推理技术的方法准确率更高,性能更佳。     

基于SWRL规则推理的隐式知识发现研究

语义网(semantic web)是当前Web的扩展,已被各个领域广泛接受,本体是语义网的关键,利用本体语言对Web上已有的信息进行更为有意义的组织和编码,从而实现机器与人之间的有效通信。语义网规则语言SWRL(Semantic Web Rule Language)是以语义的方式呈现规则的一种语言,本文首先介绍了本体构建的基本步骤,并依据此步骤构建了家庭本体,设计了针对家庭关系的SWRL规则,最后利用HermiT推理机挖掘出隐式的家庭关系。     

Identification and resolution of conflicts during ontological integration using rules

Abstract: Integration of ontologies of information sources and consumers is an important phase in achieving web‐based interoperability. The present work describes an approach for identifying certain semantic conflicts while integrating ontologies of heterogeneous information sources. This paper is focused on the identification of homonymy and synonymy between elements in ontologies. In the present work the concepts of homonymy and synonymy are synonymous to naming conflicts and entity identifier conflicts, respectively, and partial synonymy is synonymous to schema isomorphism conflicts. The concept of the mask of interoperability is introduced for the identification of synonymy. The mask of interoperability is expressed in a declarative way as a set of rules, which can then be used for resolution of conflicts during integration of ontologies. As proof of concept, ontologies are implemented using the XML‐based ontology language Ontology Web Language (OWL), and the rules are implemented using the emerging rule language Semantic Web Rule Language (SWRL). This representation in OWL and SWRL allows the ontology to be executable, flexibly extendable and platform‐independent. The OWL facts and SWRL rules are used by the Jess and Bossam reasoning engine to identify semantic homonymy and synonymy.     

Enhancing intelligence and dependability of a product line enabled pervasive middleware

To provide good support for user-centered application scenarios in pervasive computing environments, pervasive middleware must react to context changes and prepare services accordingly. At the same time, pervasive middleware should provide extended dependability via self-management capabilities, to conduct self-diagnosis of possible malfunctions using the current runtime context, and self-configuration and self-adaptation when there are service mismatches. In this article, we present an approach to combine the power of BDI practical reasoning and OWL/SWRL ontologies theoretical reasoning in order to improve the intelligence of pervasive middleware, supported by a set of Self-Management Pervasive Service (SeMaPS) ontologies featuring dynamic context, complex context, and self-management rules modeling. In this approach, belief sets are enriched with the results of OWL/SWRL theoretical reasoning to derive beliefs that cannot be obtained directly or explicitly. This is demonstrated with agents negotiating sports appointments. To cope with self-management, the corresponding monitoring, configuration, adaptation and diagnosis rules are developed based on OWL and SWRL utilizing SeMaPS ontologies. Evaluations show this combined reasoning approach can perform well, and that Semantic Web-based self-management is promising for pervasive computing environments.     

COE: A collaborative ontology editor based on a peer-to-peer framework

In this paper, we present COE, a peer-to-peer collaborative ontology editor, which supports the creation, editing, sharing, and reuse of ontologies, implemented on top of a general-purpose peer-to-peer framework, COPPEER. In large multi-disciplinary design projects, ontologies can be a critical success factor. Their collaborative creation leads to better understanding and increased information sharing between participants of a project, and economy of resources among projects. A peer-to-peer approach enables new modes of collaboration, while simplifying maintenance by propagating individual updates in shared models.     

Learning to Share Meaning in a Multi-Agent System

The development of the semantic Web will require agents to use common domain ontologies to facilitate communication of conceptual knowledge. However, the proliferation of domain ontologies may also result in conflicts between the meanings assigned to the various terms. That is, agents with diverse ontologies may use different terms to refer to the same meaning or the same term to refer to different meanings. Agents will need a method for learning and translating similar semantic concepts between diverse ontologies. Only until recently have researchers diverged from the last decade's common ontology paradigm to a paradigm involving agents that can share knowledge using diverse ontologies. This paper describes how we address this agent knowledge sharing problem of how agents deal with diverse ontologies by introducing a methodology and algorithms for multi-agent knowledge sharing and learning in a peer-to-peer setting. We demonstrate how this approach will enable multi-agent systems to assist groups of people in locating, translating, and sharing knowledge using our Distributed Ontology Gathering Group Integration Environment (DOGGIE) and describe our proof-of-concept experiments. DOGGIE synthesizes agent communication, machine learning, and reasoning for information sharing in the Web domain.     

基于SWRL的网络管理信息定义

针对当前现有的网络与系统管理信息定义语言种类多、语义和规则描述能力弱的缺陷,提出了一种在基于本体的网络管理框架中使用语义网规则语言SWRL(SemanticWebRuleLanguage)定义网络管理信息的方法。通过本体语言从语义的层面整合现有的管理信息定义语言,使用RuleML(RuleMarkupLanguage)定义管理行为的规则,提高了网络管理信息定义的表达力,为智能网管奠定了基础。     

Distributed reasoning with ontologies and rules in order-sorted logic programming

Integrating ontologies and rules on the Semantic Web enables software agents to interoperate between them; however, this leads to two problems. First, reasoning services in SWRL (a combination of OWL and RuleML) are not decidable. Second, no studies have focused on distributed reasoning services for integrating ontologies and rules in multiple knowledge bases. In order to address these problems, we consider distributed reasoning services for ontologies and rules with decidable and effective computation. In this paper, we describe multiple order-sorted logic programming that transfers rigid properties from knowledge bases. Our order-sorted logic contains types (rigid sorts), non-rigid sorts, and unary predicates that distinctly express essential sorts, non-essential sorts, and non-sortal properties. We formalize the order-sorted Horn-clause calculus for such properties in a single knowledge base. This calculus is extended by embedding rigid-property derivation for multiple knowledge bases, each of which can transfer rigid-property information from other knowledge bases. In order to enable the reasoning to be effective and decidable, we design a query-answering system that combines order-sorted linear resolution and rigid-property resolution as top-down algorithms.     

Development of a peer-to-peer information sharing system using ontologies

Most existing agent-oriented methodologies ignore system extensibility, interoperability and reusability issues. Ontologies have been found to play a significant role in facilitating interoperability, reusability, MAS development activities (including MAS analysis and agent knowledge modeling) and MAS run-time operation (including agent communication and reasoning). However, most of the existing AOSE methodologies do not provide support for ontology-based MAS development. We present software engineering requirements for ontology-based development for MAS and examine an existing methodology, MOBMAS – a “Methodology for Ontology-Based MASs”, which makes use of ontologies as a modeling tool. In this examination, we highlight how MOBMAS can be extended to utilizing ontology roles in facilitating interoperability, reusability and verification. This will be based on using MOBMAS to develop peer-to-peer (P2P) community-based information sharing application which lead us to identify ontology related steps that can be added to enhance MOBMAS. MOBMAS is used by two experienced software developers who were not authors of the methodology, to guide the development of the P2P application.     

Semantic-based approach for route determination and ontologyupdating

This paper presents a semantic approach for route determination and support for several vehicles sharing the same environment. This approach relies on designing ontologies that use a semantically rich mark-up language (OWL – Ontology Web Language) and the SWRL (Semantic Web Rule Language) rule expression set. A real-time ontology update procedure is also proposed to face unforeseen circumstances. In particular, it has been implemented in a real prototype using an ACO (Ant Colony Optimization) metaheuristic to detect road width variations. Several road crossing configurations have been tested in order to check the performance of the system. The times to calculate the route and resolve priorities at crossings allow the vehicles to navigate in real-time.     

An MDE-based methodology for closed-world integrity constraint checking in the semantic web

Ontology-based data-centric systems support open-world reasoning. Therefore, for these systems, Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) are not suitable for expressing integrity constraints based on the closed-world assumption. Thus, the requirement of integrating the open-world assumption of OWL/SWRL with closed-world integrity constraint checking is inevitable. SPARQL, recommended by World Wide Web (W3C), is a query language for RDF graphs, and many research studies have shown that it is a perfect candidate for closed-world constraint checking for ontology-based data-centric applications. In this regard, many research studies have been performed to transform integrity constraints into SPARQL queries where some studies have shown the limitations of partial expressivity of knowledge bases while performing the indirect transformations, whereas others are limited to a platform-specific implementation. To address these issues, this paper presents a flexible and formal methodology that employs Model-Driven Engineering (MDE) to model closed-world integrity constraints for open-world reasoning. The proposed approach offers semantic validation of data by expressing integrity constraints at both the model level and the code level. Moreover, straightforward transformations from OWL/SWRL to SPARQL can be performed. Finally, the methodology is demonstrated via a real-world case study of water observations data.     

A hybrid ontology approach for integration of obsolescence information

Information sharing among distributed obsolescence management systems is a challenge because of the heterogeneity of data (data with different forms and representations). Indeed, this is the main hurdle that exists for current tools managing product obsolescence. This paper presents a hybrid ontology approach for the integration of obsolescence information that combines a global ontology that provides a shared vocabulary for the specification of the semantics of obsolescence domain knowledge, along with local ontologies that describe structures of multiple data sources distributed in various obsolescence management tools. A procedure is provided for mapping local ontologies to the global ontology by quantifying relationships between classes and identifying groups of classes with a clustering method. Ontologies and rules of identifying relationships are realized with OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language). With the application of the hybrid ontology approach, a unified view of data is provided to support decision making for efficient obsolescence management and a structure where new sources of information can be easily added with little modification in the future.