语义网起源与发展研究

在对目前Web存在的主要问题进行了分析的基础上,介绍语义网,并针对语义网优势和特征进行了论述,展望了语义网的发展前景。     

语义Web中开放知识服务体系的研究

WWW是信息时代的重要标志。基于WWW的信息管理系统不仅要能运行在不同的平台上、分布的信息网络中,而且还能提供通用的平台与大量的、独立的、多类型的数据源和应用程序进行交互。开放知识服务体系OKSA就是为实现这一目标而提出的,在开放的Web资源环境中,建立动态的、跨平台的虚拟知识环境,使得人们能够获取、发布、共享和管理各种Web资源,并向用户提供按需的知识服务以支持协同工作、问题求解和决策支持等。     

语义Web中工程设计类知识表示研究

研究了如何在语义Web中,实现工程设计类知识的表示与应用。对工程设计类各种异构知识进行统一描述,在此基础上,运用RDF(S)技术,建立了语义Web环境下,工程设计类知识的Ontology。提出了基于语义Web的知识存储模型以及面向上层应用程序的接口设计,为语义Web环境下工程设计类知识管理系统的开发提供了底层平台。     

ViSWeb - the Visual Semantic Web: unifying human and machine knowledge representations with Object-Process Methodology

The Visual Semantic Web (ViSWeb) is a new paradigm for enhancing the current Semantic Web technology. Based on Object-Process Methodology (OPM), which enables modeling of systems in a single graphic and textual model, ViSWeb provides for representation of knowledge over the Web in a unified way that caters to human perceptions while also being machine processable. The advantages of the ViSWeb approach include equivalent graphic-text knowledge representation, visual navigability, semantic sentence interpretation, specification of system dynamics, and complexity management. Arguing against the claim that humans and machines need to look at different knowledge representation formats, the principles and basics of various graphic and textual knowledge representations are presented and examined as candidates for ViSWeb foundation. Since OPM is shown to be most adequate for the task, ViSWeb is developed as an OPM-based layer on top of XML/RDF/OWL to express knowledge visually and in natural language. Both the graphic and the textual representations are strictly equivalent. Being intuitive yet formal, they are not only understandable to humans but are also amenable to computer processing. The ability to use such bimodal knowledge representation is potentially a major step forward in the evolution of the Semantic Web.Received: 14 December 2002, Accepted: 28 November 2003, Published online: 6 February 2004Edited by: V. AtluriDov Dori: dori@ie.technion.ac.il     

Semantic Web computing in industry

The Semantic Web has attracted significant attention during the last decade. On the one hand, many research groups have changed their focus towards Semantic Web research and research funding agencies particularly in Europe have explicitly mentioned Semantic Web in their calls for proposals. On the other hand, industry has also begun to watch developments with interest and a number of large companies have started to experiment with Semantic Web technologies to ascertain if these new technologies can be leveraged to add more value for their customers or internally within the company, while there are already several offers of vendors of Semantic Web solutions on the market. The essence of the Semantic Web is to structure Web-based information to make it more interoperable, machine-readable and thereafter to provide a means to relate various information concepts more easily and in a reusable way. The Semantic Web acts as an additional layer on the top of the Web, and is built around explicit representations of information concepts and their relationships such as ontologies and taxonomies. Furthermore, Semantic Web technologies are not only valuable on an open environment like the Web, but also in closed systems such as in industrial settings. Hence, these technologies can be efficiently deployed for domains including Web Services, Enterprise Application Integration, Knowledge Management and E-Commerce, fulfilling existing gaps in current applications. This paper focuses on this synthesis between Semantic Web technologies and systems problems within industrial applications. There will be a short review of Semantic Web standards, languages and technologies followed by a more detailed review of applications of Semantic Web computing in industry. The paper covers theoretical considerations as well as use cases and experience reports on the topic, and we also present some current challenges and opportunities in the domain.     

Web本体语言OWL

随着对语义Web研究的深入,人们越来越关注在Web上信息内容的表示和检索问题。在语义Web的七层模型中,建立在RDF模式层之上的本体语言层用于形式化描述Web文档中词汇的含义,是建立语义Web的关键环节。该文介绍了W3C最新给出的Web本体语言OWL,给出TOWL3个子语言构造成分的含义说明,并比较了3种子语言间的差别。     

Supporting concurrent ontology development: Framework, algorithms and tool

We propose a novel approach to facilitate the concurrent development of ontologies by different groups of experts. Our approach adapts Concurrent Versioning, a successful paradigm in software development, to allow several developers to make changes concurrently to an ontology. Conflict detection and resolution are based on novel techniques that take into account the structure and semantics of the ontology versions to be reconciled by using precisely-defined notions of structural and semantic differences between ontologies and by extending state-of-the-art ontology debugging and repair techniques. We also present ContentCVS, a system that implements our approach, and a preliminary empirical evaluation which suggests that our approach is both computationally feasible and useful in practice.     

P2P中基于本体论的知识管理框架模型及实现

为了将P2P中对等体的资源描述为结构化的知识,以提高资源共享,本文提出一个基于本体论的知识管理框架模型。从知识的建立和知识的检索两方面分析了模型的实现技术。探讨了相互协作的对等体按预定义查询模式和本体论匹配的语义技术实现信息搜索和知识获取的过程。     

Extending the Unified Modeling Language for ontology development

There is rapidly growing momentum for web enabled agents that reason about and dynamically integrate the appropriate knowledge and services at run-time. The dynamic integration of knowledge and services depends on the existence of explicit declarative semantic models (ontologies). We have been building tools for ontology development based on the Unified Modeling Language (UML). This allows the many mature UML tools, models and expertise to be applied to knowledge representation systems, not only for visualizing complex ontologies but also for managing the ontology development process. UML has many features, such as profiles, global modularity and extension mechanisms that are not generally available in most ontology languages. However, ontology languages have some features that UML does not support. Our paper identifies the similarities and differences (with examples) between UML and the ontology languages RDF and DAML+OIL. To reconcile these differences, we propose a modification to the UML metamodel to address some of the most problematic differences. One of these is the ontological concept variously called a property, relation or predicate. This notion corresponds to the UML concepts of association and attribute. In ontology languages properties are first-class modeling elements, but UML associations and attributes are not first-class. Our proposal is backward-compatible with existing UML models while enhancing its viability for ontology modeling. While we have focused on RDF and DAML+OIL in our research and development activities, the same issues apply to many of the knowledge representation languages. This is especially the case for semantic network and concept graph approaches to knowledge representations. Initial sbmission: 16 February 2002 / Revised submission: 15 October 2002 Published online: 2 December 2002     

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.     

描述逻辑综述

描述逻辑是一种知识表示的形式化语言,是一阶逻辑的可判定子集。作为一种知识表示的有效机制,描述逻辑被广泛地应用到计算机科学的许多领域中。本文对目前描述逻辑的研究与应用现状进行了综述性的介绍,并且从描述逻辑的定义、描述逻辑的基本语法及语义、体系结构以及描述逻辑在语义Web中的地位等方面做了系统阐述。     

语义网环境下的知识集成系统设计

语义网近年来发展迅速,为网络环境下实现知识集成提供理论支撑和技术路线,可以为知识数据建立关联并增强系统的可扩展性。在资源描述框架下构建知识本体,采用Java语言和Jena API对知识集成系统进行设计和开发,构建知识集成框架实现知识内容显示和关联查询。系统设计突出了语义网的功能和特色,应用多种语义网体系技术和工具,提高知识集成系统的数据分析能力和用户体验效果。     

Development of technology for customer requirement-based reference design retrieval

Engineering design is a knowledge-intensive process, and includes conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each task involves various aspects of knowledge and experience. Whether this knowledge and experience can be effectively shared is key to increasing product development capability and quality, and also to reducing the duration and cost of the development cycle. Therefore, offering engineering designers various query methods for retrieving engineering knowledge is one of the most important tasks in engineering knowledge management.The study develops a technology for customer requirement-based reference design retrieval to provide engineering designers with easy access to relevant design and associated knowledge. The tasks involved in this research include (i) designing a customer requirement-based reference design retrieval process, (ii) developing techniques related to the technology for customer requirement-based reference design retrieval, and (iii) implementing a customer requirement-based reference design retrieval mechanism. The retrieval process comprises the steps of customer requirement-based query, case searching and matching, and case ranking. The technology involves (1) a structured query model for customer requirement, (2) an index structure for historical design cases, (3) customer requirement-based case searching and matching mechanisms, (4) a customer requirement-based case ranking mechanism, and (5) a case-based representation of designed entities.     

Ontology-based enterprise knowledge integration

Enterprises are getting more knowledge intensive, and the integration of various types of knowledge becomes a challenge. It has been accepted that ontology is an important concept for knowledge integration. In this paper, three issues have been addressed: (i) ontology construction which includes the method and implementation of a Concept Map based ontology construction, and the evaluation of the constructed ontology; (ii) a dynamic workflow, in which an ontology-based workflow system is used to accumulate knowledge during the business process, and (iii) the rules and constraints used for knowledge representation, in which a Semantic Web Rule Language (SWRL) is used to group the rules and constraints into different classes executed by a inference engine. Two cases have been studied using the above methods and tools. Case one is an acquisition prototype for the aircraft industry. The other is for an on-going bar code management project carried out by this research team. Both cases show that the developed methods can be used for knowledge integration.     

Semantic Web based innovative design knowledge modeling for collaborative design

This paper describes a study about how to use the Semantic Web technologies for innovative design knowledge modeling in a multi-agent distributed design environment. Semantic Web based knowledge modeling for innovative design is proposed as prelude to the meaningful agent communication and knowledge reuse for collaborative work among multidisciplinary organizations. A model for innovative design is proposed at first, based on which a knowledge schema is brought forward. For sharing the design knowledge among an internet-based or distributed work team, even globally, A RDF-based knowledge model is presented to realize its representation on Semantic Web. A Semantic Web based repository for innovative design and its API for topper Semantic Web applications have been also constructed. The proposed knowledge modeling extends traditional product modeling with capabilities of innovative design, knowledge sharing and distributed problem solving, and is employed as a content language within the messages in the proposed multi-agent system architecture. The proposed approach is viewed as a promising knowledge management method that facilitates the implementation of computer supported cooperative work in innovative design of Semantic Web applications.     

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.