基于参与者上下文概念意图的语用Web服务发现

为了使得语义Web服务的发现结果与服务请求者的意图更加一致,提高服务发现的准确性,改善服务发现和选择的自动化性能。在服务描述中增加了对于服务提供者和服务请求者的上下文知识的表示,使用规划的方法完成服务参与者之间对于私有的上下文本体概念意图的理解。实验表明,该方法能够有效提高发现的准确性,在使用标准服务测试集进行服务发现实验时,尽管概念规划使得服务发现时间有所增加,但服务发现的准确性得到很大提高,尤其对于描述服务领域本体语义差异较大的情况,服务发现的结果更为准确。     

OntoPipeliner: An ontology-based automatic semantic service pipeline generator

The Web is a distributed environment rich with Web services going through continual metamorphosis; thus, sustaining semantic stability of service composition has become a major challenge. Automatic service composition – enabled both by the use of ontologies that describe service domains and by user-specified constraints bound to the ontologies – provides us candidate service pipelines at composition design time. The ontology-based languages for semantically describing web services, such as OWL-S, have been widely used. Though rich and comprehensive in their expressiveness, the use of these languages still leaves much of composition process manual. In this work, we present an ontology-based semantic web service composition system called OntoPipeliner. It employs a novel way of utilizing characteristics of Web services that reflect the classes and properties of domain ontologies and provides the ontology-guided constraints for automatic composition of services, in order to guide the user toward the best pipeline that meets the user requirements.     

基于多本体的语义Web服务发现研究

随着大量Web服务的出现,迫切需要高效的服务发现方法。语义Web服务将Web服务和语义相结合,充分利用语义增强Web服务。现有的语义Web服务发现研究中,大多采用同一本体描述服务需求方和提供方的知识。而现实世界里,很多时候服务需求方和服务提供方采用了不同的本体。针对多本体下的语义Web服务发现问题,给出了一种新的计算不同本体概念相似性的算法,提出了基于多本体的语义Web服务发现方法。实验结果表明了该方法的有效性。     

支持Web服务组合与验证的形式化模型

针对Web服务的组合与验证问题,在范畴理论描述框架的基础上,引入进程代数描述服务组件的外部行为,为Web服务系统的架构描述建立了一种形式化的语义模型。Web服务作为范畴理论中的对象节点,服务间的交互和组合关系作为态射,从而以范畴图表的形式来描述服务网络。在形式化定义服务接口、Web服务、服务组合等概念的基础上,进一步分析讨论了服务组合和交互过程中的语义特性,给出了Web服务可替代性和服务请求可满足性的形式化定义。实例研究表明,该框架增强了Web服务架构的语义描述能力。     

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.     

一种基于随机PETRI网的OWL-S量化描述模型

OWL-S是一种面向领域本体的语义Web服务组合描述语言,也是一种可自动机器解释的语义标记语言,同时实现了Web服务功能和服务间互操作、互调用、互协作的语义化描述,是目前最重要的服务组合标准之一。提出了一种基于非马尔科夫随机PETRI网(NMSPN)的概率模型,对OWL-S描述的Web服务的控制流进行了建模和描述,并在NMSPN流程模型基础上建立了一系列的概率分析方法,实现了对语义Web服务的量化可信性的分析。     

Extracting semantic relations to enrich domain ontologies

Domain ontologies facilitate the organization, sharing and reuse of domain knowledge, and enable various vertical domain applications to operate successfully. Most methods for automatically constructing ontologies focus on taxonomic relations, such as is-kind-of and is-part-of relations. However, much of the domain-specific semantics is ignored. This work proposes a semi-unsupervised approach for extracting semantic relations from domain-specific text documents. The approach effectively utilizes text mining and existing taxonomic relations in domain ontologies to discover candidate keywords that can represent semantic relations. A preliminary experiment on the natural science domain (Taiwan K9 education) indicates that the proposed method yields valuable recommendations. This work enriches domain ontologies by adding distilled semantics.     

基于本体聚类的面向业务用户服务发现模型

现有的基于语义的服务发现机制都存在着缺陷和不足，该文提出一种面向业务用户的、基于本体聚类的Web服务发现模型，应用本体聚类算法对领域本体和Web服务进行分层管理，实现了以业务用户为中心的设计思想。     

基于本体的语义Web挖掘技术研究

为提高web服务的个性化系统服务水平,解决现有的Web服务缺少形式语义支撑,改善Web挖掘效果,提出了一个基于本体的语义Web挖掘模型,并对其基于本体论的语义和生成过程进行了详细论述,对提高Web服务个性化系统的效率和精度作了有益探讨。     

面向服务环境下基于本体映射的多领域业务过程协同*

为解决面向服务环境下多领域业务过程协同中的语义不一致问题,使不同领域提供的Web服务实现无障碍交互以及数据和知识共享,提出基于本体映射的多领域业务过程协同框架。首先根据领域知识建立参考本体,然后根据各领域的参考本体生成领域间的协同本体,最后将协同本体通过映射转换到BPEL和WSDL文件。该方法能够保留流程与Web服务中的原始语义信息,从而保证不同领域业务过程协同地顺利进行。原型系统在欧盟ImportNET项目中得到了验证。     

A model-driven approach to building modern Semantic Web-Based User Interfaces

The Semantic Web has widely spread in the last 10 years as a suitable web platform to support semantics and expressive information seeking. However, one of the main problems with this paradigm is still the representation and manipulation of ontologies as well as the complex relationships that they implicitly represent. Actually, this remains a challenge when unskilled users have to deal with this abstract representation in order to carry out daily solving-problem activities (e.g., designing web applications based on ontologies). This probably made the Semantic Web to decrease in popularity, also being commercially unsupported and overcame by recent technologies and services based on the Web 2.0, the emerging end-user-focused web concept. All in all, the specification of Model-Based User Interfaces fits very well to both paradigms. Accordingly, the aim of this work is to provide new ways of modeling user interfaces based on semantic models that better fit the domain problem. At the same time, we think of exploiting interactive features through current and modern end-user programming elements based on the Web 2.0, finally contributing to an architecture that supports higher interactive end-user interfaces on the web.     

基于功能语义的Web服务发现方法

随着Web服务技术的发展与应用,基于功能语义进行Web服务发现已经逐渐成为服务使用者最为迫切的需求.而现有的服务发现机制还不能很好地解决这一问题.所以提出了一种基于功能语义的Web服务发现方法.通过定义Web服务功能描述模型,规范服务提供者和使用者对Web服务功能的描述;同时构建了领域功能本体,提出语义标注的机制,从而让用户可以基于功能语义发现Web服务.并设计了基于功能语义的Web服务描述语言,构建了原型系统,为基于功能语义进行服务发现提供了一种有效可行的方法.     

Understanding as We Roam

Increasingly, the problem for roaming users isn't discovering local Web services or local context information or even getting their applications to intemperate with them at a syntactic level, but rather achieving interoperation at a semantic level. Developers are beginning to use semantic Web technologies such as ontologies to expose the semantics of context models and Web services. However, different ontologies arise due to natural human diversity in modeling domains. It's therefore important to develop mappings between ontologies. This article describes a practical ontology-mapping process specified in the Unified Modeling Language, as well as its deployment     

本体驱动的语义Web服务动态复合的研究

传统Web服务的复合由于缺乏足够的语义信息而大大降低了服务复合的效率和准确率。语义Web弥补了传统Web语义不足的缺点。但是,面对语义Web上分布的海量知识,如何有效地利用语义信息实现Web服务复合成为一个迫切需要解决的问题。文章针对这一问题,提出一种基于多维用户模型的动态服务复合机制。该机制在Web服务语义标识的启发下通过语义匹配算法能够实现Web服务的顺序复合和并行复合。采用这种服务复合机制将会在一定程度上提高语义Web服务复合的效率和准确率。     

基于语义描述的分布式Web服务发布与发现

结合P2P与Web服务语义描述技术，提出了一种基于分布式哈希表的非集中式Web服务发布与发现方法。通过定义服务供求双方共同遵守的领域本体，实现具有同样语义概念的两种不同描述的统一，提高服务发现的效率和准确度。利用类别本体对领域本体的组织，提出了层次式Web服务目录系统。基于该系统，服务的发布与发现是在特定应用领域范围内进行，因此减少了服务搜索空间，提高了服务发现的效率。