CRL:对语义Web上的Ontology表示语言DAML+OIL的一种扩充方案

Ontologies在语义Web中起着举足轻重的作用,它不仅能为人类用户而且能为软件Agent提供从语法层次到语义层次上的互操作性。DAML+OIL是专门为语义Web设计的一种Ontology描述语言,它将框架系统、描述逻辑和Web标准这三个不同领域的优点结合了起来,采用面向对象的方法用类和属性来描述领域的结构。但是DAML+OIL也有不足之处,其一是约束表达能力较弱,只能表示属性值的基数约束,不能表示属性值的区间约束;其二是不能表示任何规则,而无论是约束表示还是规则表示对Ontology都是非常重要的。该文提出一种对DAML+OIL的扩充方案,使得扩充后的DAML+OIL可以表示简单的规则和属性值的区间约束。     

DAML+OIL: an ontology language for the Semantic Web

By all measures, the Web is enormous and growing at a staggering rate, which has made it increasingly difficult-and important-for both people and programs to have quick and accurate access to Web information and services. The Semantic Web offers a solution, capturing and exploiting the meaning of terms to transform the Web from a platform that focuses on presenting information, to a platform that focuses on understanding and reasoning with information. To support Semantic Web development, the US Defense Advanced Research Projects Agency launched the DARPA Agent Markup Language (DAML) initiative to fund research in languages, tools, infrastructure, and applications that make Web content more accessible and understandable. Although the US government funds DAML, several organizations-including US and European businesses and universities, and international consortia such as the World Wide Web Consortium-have contributed to work on issues related to DAML's development and deployment. We focus on DAML's current markup language, DAML+OIL, which is a proposed starting point for the W3C's Semantic Web Activity's Ontology Web Language (OWL). We introduce DAML+OIL syntax and usage through a set of examples, drawn from a wine knowledge base used to teach novices how to build ontologies.     

语义Web语言DAML＋OIL及其应用初探

1.引言 1.1 产品信息集成的现状和面临的局限产品信息描述格式的不统一使得传统CIMS之间产品信息不能共享,数据交换产生障碍。STEP标准及其EXPRESS语言统一了产品信息的建模标准和数据结构,使得产品信息由原来的机器不可读(machine-unreadable)变为机器可读(machine-readable),从而在数据格式上解决了产品信息的共享和交换问题。但是,分布、开放、动态的计算环境,使得企业内部及企业     

Semantic Web services

The authors propose the markup of Web services in the DAML family of Semantic Web markup languages. This markup enables a wide variety of agent technologies for automated Web service discovery, execution, composition and interoperation. The authors present one such technology for automated Web service composition.     

利用Prolog实现语义网中的知识推理

元数据的交换是实现语义网应用的基础。在语义网的架构中,Ontology语言利用自己的元级描述能力来建立元数据之间的联系,从而实现语义的交换。本文分析了DAML OIL语言的知识描述能力,并对它蕴含的关于类的知识建立了Prolog的推理规则,最后结合XSBProlog推理引擎和InterProlog接口用Java语言实现了对Ontology的推理,从而实现了不同Ontology之间的元数据交换。     

DAMLJessKB: a tool for reasoning with the Semantic Web

Fully realizing the Semantic Web vision will require practical tools. We believe that DAMLJessKB is one such tool. As more and more Web sites, network services, databases, and knowledge bases look to DAML as a de facto representation syntax, we hope that DAMLJessKB will become one in a suite of tools that let users truly leverage the shared semantics.     

ITtalks: a case study in the Semantic Web and DAML+OIL

Semantic Web markup languages will improve the automated gathering and processing of information and help integrate multiagent systems with the existing information infrastructure. The authors, describe their ITtalks system and discuss how Semantic Web concepts and DAML+OIL extend its ability to provide an intelligent online service.     

Web本体语言的分析与比较

本语言用于形式化描述Web文档中词汇的含义,在语义Web的7层模型中占有重要的位置。目前不同的组织提出了多种本体建模语言：RDF,RDFS,OIL,DAML OII和OWL。在介绍这些本体语言的基础上对它们进行了分析和比较,指出了它们相对某些关键特性的差异。     

Named graphs

The Semantic Web consists of many RDF graphs nameable by URIs. This paper extends the syntax and semantics of RDF to cover such named graphs. This enables RDF statements that describe graphs, which is beneficial in many Semantic Web application areas. Named graphs are given an abstract syntax, a formal semantics, an XML syntax, and a syntax based on N3. SPARQL is a query language applicable to named graphs. A specific application area discussed in detail is that of describing provenance information. This paper provides a formally defined framework suited to being a foundation for the Semantic Web trust layer.     

Semantic Web研究综述

近年来,Semantic Web逐渐成为WWW领域的研究热点以及智能化网络服务和应用开发中的关键技术之一。归纳了Semantic Web技术的研究背景和主要发展历史。在分析了典型的Semantic Web概念后,给出了Semantic Web的定义。通过讨论Semantic Web构想的层次框架模型,指出了各个层次扮演的角色,并着重分析了Semantic Web的重要研究领域,指出了它们在Semantic Web构架中的核心作用。通过分析Semantic Web的应用领域和相关开发工具以及面临的问题和挑战,指明了Semantic Web研究和实践的方向。作为总结,给出了Semantic Web领域下一步的研究趋势。     

XML Schema，RDF Schema及DAML比较

以语义Web的层次为出发点,比较XML Schema,RDF Schema及DAML的功能和作用。从描述语言表达能力的各个方面,比较这三种语言的关系及差异。     

Composition of Semantic Web services using Linear Logic theorem proving

This paper introduces a method for automatic composition of Semantic Web services using Linear Logic (LL) theorem proving. The method uses a Semantic Web service language (DAML-S) for external presentation of Web services, while, internally, the services are presented by extralogical axioms and proofs in LL. LL, as a resource conscious logic, enables us to capture the concurrent features of Web services formally (including parameters, states and non-functional attributes). We use a process calculus to present the process model of the composite service. The process calculus is attached to the LL inference rules in the style of type theory. Thus, the process model for a composite service can be generated directly from the complete proof. We introduce a set of subtyping rules that defines a valid dataflow for composite services. The subtyping rules that are used for semantic reasoning are presented with LL inference figures. We propose a system architecture where the DAML-S Translator, LL Theorem Prover and Semantic Reasoner can operate together. This architecture has been implemented in Java.     

应用于电子商务的语义Web核心语言分析

到目前为止已有多种基于语义Web的语言，这些语言实现了基于Web的知识表示、共享和重用。重点分析了语义Web的几种语言：XML规范簇、RDF、RDF Schema、DAML OIL。在此基础上给出了语义Web技术的重要应用——电子商务中核心语言的分层结构。该结构中XML规范簇完成了数据描述功能，RDF用于描述元数据，RDF Schema提供了基本的本体原语，DAML OIL提供了推理功能，利用这些语言，可以实现电子商务中数据描述的统一性、通用性及互操作性。     

领域自适应的Web服务评价模型

Web服务质量的评价是指导Web服务的选取与组合的主要手段,而目前的Web服务评价模型采用与服务领域无关的评价因子来评价服务,不能全面衡量服务使用者对Web服务质量的要求．该文用基于语义的方法描述Web服务评价模型,支持动态定制不同领域的服务评价因子,同时利用Web服务在使用过程中产生的知识以及领域专家的领域知识交互计算评价因子的权重分布．实验证明,该模型的评价结果优于其它评价模型的评价结果,并且采用交互算法的准确率比仅采用机器学习算法或仅使用先验知识的准确率提高10％以上．该模型可应用于Web服务管理系统、Web服务选取和Web服务合成引擎等Web服务应用系统中．