Semantic Web与Agent的共生及融合

Web技术与Agent技术作为两种技术体系一直独立发展.但现在Web技术借鉴Agent技术的先进思想,基于Ontology对Web进行改造,提出了Semantic Web的概念.在Internet上必将是Semantic Web和Agent共同提供智能化、个性化的服务.而要想达到这个目的,首先必须解决Ontology的构造问题.文中在详细论述Semantic Web和Agent的基础上,探讨了Semantic Web与Agent的共生及融合关系,给出了共生及融合关系图,并设计了一个概念性的智能Web服务IWS模型.     

Semantic Web与Agent的共生及融合

Web技术与Agent技术作为两种技术体系一直独立发展。但现在Web技术借鉴Agent技术的先进思想，基于Ontology对Web进行改造，提出了Semantic Web的概念。在Internet上必将是Semantic Web和Agent共同提供智能化、个性化的服务。而要想达到这个目的，首先必须解决Ontology的构造问题。文中在详细论述Semantic Web和Agent的基础上，探讨了Semantic Web与Agent的共生及融合关系，给出了共生及融合关系图，并设计了一个概念性的智能Web服务IWS模型。     

基于分布RDF(S)模型的信息查询与集成

在Web应用环境中,可以通过RDF(S)形式描述企业领域内分布信息资源的语义,以提高信息查询的准确性.提出了描述分布异构RDF(S)的分布RDF(S)模型,并基于这一模型给出了实现分布RDF(S)查询的方法,此查询方法既能实现实例层次的查询,也能实现概念层次的查询.基于这一方法,用户能够以统一的形式来查询,获取相关的信息资源,同时还可以实现分布RDF(S)的集成.     

f-NSWRL:一种语义Web非单调模糊规则语言

现实世界中存在着大量的不精确和不确定知识和信息.在语义Web中表示模糊规则是语义Web领域的重要研究问题之一.作为模糊语义Web规则语言,f-SWRL(fuzzy Semantic Web Rule Language)仅能表达单调的模糊规则,不能表示非单调的模糊规则.为了表示现实世界中人类知识和推理的非单调性,本文提出一种新的模糊规则语言--f-NSWRL (fuzzy Nonmonotonic Semantic Web Rule Language),对两种否定(即否定(negation)和负即失败(negation as failure))在其中的应用进行了研究,讨论了优先级问题来处理模糊知识库中的规则冲突问题,给出了在竞争规则中计算优先级的法则.为了使规则互换格式RuleML(Rule Markup Language)在f-NSWRL与其他规则语言进行规则互换时起到中间语言的作用,本文对RuleML进行了非单调和优先级两方面的扩展.     

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UPPAAL的AADL行为模型验证方法研究

Web服务(Web services)已成为当前和未来网络分布式应用的主流软件开发技术。如何确保Web服务软件的质量和可靠性是当前软件工程领域关注的焦点问题。分析了Web服务测试的层次和阶段,以及测试工具的现状,提出了Web服务自动化测试的技术框架,分析了此框架内Web服务操作、Web服务操作序列和Web服务组合WSB-PEL流程测试的关键技术,并研制了测试用例自动生成的原型系统,给出了实验结果,最后指出Web服务自动化测试技术值得进一步探讨的主题。     

从关系数据库到RDF的转换

随着语义Web的快速发展,利用已有的数据资源来构建本体受到了很大程度的重视。因此,作为资源描述框架的RDF在语义Web中的地位就显得越来越重要。由于大量的数据都存储在关系数据库里面,因此如何将关系数据库中的数据转换为RDF成为一个亟待解决的问题。提出了一种能自动将关系数据库数据转换为RDF的方法,同时给出了详细的映射规则和转换过程,并通过一个实例验证了该方法的可行性。     

RDF 数据查询处理技术综述

随着语义网以及信息抽取技术等研究的发展,Web上涌现出越来越多的RDF数据,海量RDF数据的管理,已经成为学术界和工业界研究的热点之一。从RDF数据集形态及RDF数据组织存储两个维度以及查询表述、查询处理、查询优化等方面,深入地分析和比较了RDF数据查询处理方法,并在此基础上提出了未来研究的方向和挑战。     

RDF数据浏览的研究综述

随着语义网的快速发展,目前Web上语义网数据已经达到相当的规模,成为重要的信息和知识来源.因此,RDF数据浏览的研究开始得到广泛关注.通过对比传统Web信息浏览和RDF数据浏览两个问题,指出RDF数据浏览的5个重要问题:确定浏览子图的模式、数据的收集、大规模数据的处理、数据的组织方式以及数据的呈现方式.基于这些挑战,我们调研了多个系统和不同的解决方案.最后,总结了目前的研究现况,讨论存在的挑战,并提出未来的研究方向.     

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。     

基于语义的Web挖掘

基于语义的Web挖掘是使用从现有Web数据中抽取的语义或直接使用Web数据中已有的语义结构来帮助Web挖掘。它有效地结合了语义网和Web挖掘两个领域的研究成果,既可以通过开发新的语义结构来帮助Web挖掘,又可以利用挖掘结果促进语义网的创建。本文介绍了基于语义的Web挖掘的基本思想和研究现状,分析了语义网和Web挖掘相结合的优势,并详细论述了国际上关于利用数据挖掘技术创建语义网,利用语义挖掘Web数据和直接挖掘语义网三个方面的研究工作。     

WritingResearchWriting: The Semantic Web and the Future of the Research Project

In this essay, I explore one advancement in particular—the Semantic Web—and discuss ways in which it stands to change students’ interaction with information in digital spaces, and how new forms of interaction could impact the teaching of writing. I go back to the earliest days of the Web in order to remind readers how information retrieval has evolved in the digital age. I also provide a general discussion of the vision, current state, and possible futures of the Semantic Web, and I focus on how the Semantic Web might alter the research process and, more importantly, the research-writing relationship. I also offer suggestions for teaching composition in advance of and for the Semantic Web. Although the Semantic Web is still several years off, I contend that research and writing will merge into a single process, thus presenting new opportunities for the teaching of writing then and, perhaps more importantly, now. These opportunities include helping students to identify the challenges of information retrieval and overload, to see research as more about establishing links and connections between information sources and less about finding the “right” sources, and to write for the Semantic Web—and, in doing so, teach students that researching and writing are inseparable.     

The two cultures: Mashing up Web 2.0 and the Semantic Web

A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. A closer look, though, reveals that the core technologies and concerns of these two approaches are complementary and that each field can and must draw from the other’s strengths. We believe that future Web applications will retain the Web 2.0 focus on community and usability, while drawing on Semantic Web infrastructure to facilitate mashup-like information sharing. However, there are several open issues that must be addressed before such applications can become commonplace. In this paper, we outline a semantic weblogs scenario that illustrates the potential for combining Web 2.0 and Semantic Web technologies, while highlighting the unresolved issues that impede its realization. Nevertheless, we believe that the scenario can be realized in the short-term. We point to recent progress made in resolving each of the issues as well as future research directions for each of the communities.     

一个语义Web构架及其实现

语义Web是国际互联网组织W3C制定的关于未来Web的一个长远蓝图,近两年发展异常迅猛,并显示出诱人的应用前景。该文在概述语义Web基本技术的基础上,设计了一个面向企业门户网站的语义Web体系结构;提出了页面代理的概念及其作用与功能结构;设计了语义Web查询语言CDQL,该语言在跨信息源查询、约束表示等方面扩充了DQL查询语言。     

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 Mining: State of the art and future directions

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: More and more researchers are working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use of Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself.The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.     

Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data – loosely also known as Linked Data – which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web – in terms of scale, unreliability, inconsistency and noise – are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.     

Using the Semantic Web for linking and reusing data across Web 2.0 communities

Large volumes of content (bookmarks, reviews, videos, etc.) are currently being created on the “Social Web”, i.e. on Web 2.0 community sites, and this content is being annotated and commented upon. The ability to view an individual's entire contribution to the Social Web would be an interesting and valuable service, particularly important as social networks are often being formed through created content and things that people have in common (“object-centred sociality”). SIOC is a Semantic Web research project that aims to describe online communities on the Social Web. This paper describes how SIOC and the Semantic Web can enable linking and reuse scenarios of data from Web 2.0 community sites, and introduces a SIOC Types module to further specify the type of content items and act as a “glue” between user posts and the content items created and annotated by users.     

基于语义Web上知识表示的研究及其应用

随着对语义研究的深入,人们越来越关注在W EB上信息内容的表示问题,通过分析语义W EB上知识表示的特点后指出,以RDF为基础的知识表示语言可较好地实现语义W EB的知识表示。最后通过语义W EB上的语义检索应用给予了说明。     

基于本体的语义Web研究

语义Web与本体的关系极为特殊,本体在语义Web本身的体系结构中扮演着极为重要的角色,同时,位于语义Web体系结构的其它层的XML、RDF(S)等与本体也有着千丝万缕的联系。为阐述两者的关系,探讨基于本体的语义Web的特点及应用,介绍了本体和语义Web的产生和发展,在此基础上对基于本体的语义Web进行研究,重点分析了本体在描述语义方面弥补了XML、RDF(S)等的不足,并结合Web服务检索的实例介绍了本体在Web服务上的应用。