基于履带式本体构建方法的多代理模型研究

本体工程为本体构建提供与其相适应的本体开发方法。履带式本体构建方法具有较强的适应性,能够针对本体的不同规模来指导本体开发操作,并对开发过程进行评估。为提高本体构建效率,利用多代理的分布性、自治性、协作性等特点,构建了支持履带式本体开发方法的多代理模型,对其中的代理、通信和代理之间的协作进行了形式化定义和描述,并实现了代理操作、协作等相关算法和代理运行平台。     

一种果品领域本体库的构建方法

果品领域知识涉及到的学科知识多、知识量大,如何使这些知识得到共享和重用,目前仍是一个重要的挑战,通过构建果品领域本体库来解决这一问题.本体是一种知识重用、知识共享和建模的重要工具.果品领域本体库是果品领域本体的集合;果品领域本体是果品领域知识中概念、属性、过程及相互关系的形式化描述,这种形式化描述使知识可以重用和共享,让计算机能够理解;为人与人之间、组织与组织及计算机之间通信提供了统一的术语与概念,使知识共享成为可能,同时也有利于知识的获取,可提高获取的速度和可靠性.     

本体构建研究综述

本体是目前信息处理领域研究热点.通过对本体构建方法和工具的综述,对其研究中的关键问题进行了讨论,并在此基础上分析比较了各种本体构建方法和工具,最后,对研究现状中存在的瓶颈问题进行了总结,并提出了未来的研究方向.     

药学本体构建实践

分析了药学本体构建的意义,介绍了药学本体构建工具和构建的原则,使用protégě本体编辑器,并借鉴七步法构建思路,详细阐述了药学本体每一步骤的构建过程,包括药学本体需求分析,复用现有本体的可能性分析,药学领域知识的结构化分析和核心概念集的获取,药学本体类、属性和实例的定义.本文的药学本体已应用在基于本体的中文元搜索引擎查询结果自动分类系统中,并能通过系统的运行实现本体的进化.     

一种基于经典领域本体构建方法的改进研究

本文通过对现有经典领域本体构建方法的优点及缺点的分析,对本体构建方法做了一些积极的探索,并提出了一种新的本体构建模型。     

一种关系数据库到本体的自动构建方法

随着语义网的发展,对本体的需要也越来越大。但是目前大多数的数据被存储在关系数据库中,这些数据不能被语义网应用程序所访问。因此如何将关系数据中的数据转化为可以被语义网应用的数据,是一个需要解决的问题。针对上述问题,提出了一种从数据库自动地构建OWL本体的方法。该方法把本体构建过程分为语义信息的发现和本体映射两个部分。并且定义了一种图M-Graph,通过M-Graph的生成与分析,结合映射规则自动地构建OWL本体。实验验证,该方法可自动地由关系数据库构建OWL本体,并且可以得到相对丰富和准确的本体。     

一种领域本体构建方法及其在相片管理中的应用

自20世纪90年代以来,本体逐渐被应用到很多领域,本体的构建方法论也成为国内外机构的热门研究课题。在分析和总结现有的本体构建经验的基础上,提出了一种领域本体的构建方法,它符合人们的思维认知规律,可操作性和扩展性强。并使用该方法为相片管理领域进行本体建模,实验表明了该方法的科学性和有效性。     

领域本体构建方法研究

通过分析现有拳体构建方法的局限性,提出了一种新的本体构建方法。该方法论述了本体构建过程．解决了现实领域知识到计算机可以理解的形式化编码的转换问题。     

石油勘探开发领域本体构建及应用

领域本体是知识工程中的重要组成部分,本体技术是一种重要的知识表示方法,是知识工程背后的支撑技术。首先介绍领域本体的构建理论及方法,从主题域、知识域、本体域提出石油勘探开发领域本体的三维知识模型并基于该模型开发了本体构建软件实现了石油勘探实例的管理及应用。     

军事领域本体构建研究

在仿真系统的研究过程中,面临军事领域知识获取及不同应用之间的互操作等问题.这些难题的背后实际是技术人员和军事人员之间理解一致性和机器之间理解一致性的问题.本体是关于事物本质的模型,已被广泛应用于知识分类、表达、共享及重用等方面.首先,讨论了本体的概念并给出了领域本体构建的一套通用原则和方法.然后详细分析了军事领域本体所包含的各方面知识元素,包括作战单元类、单元之间的关系、交战行为、交战规则、武器装备、作战计划等,并分别给出了它们的简单表示结构.最后概要讨论了多个本体合并时的本体检验问题.标准化的军事知识表示结构可以为技术人员和军事人员之间的交流提供统一的认识和参照,为机器之间的互操作提供一种"语言",从而消除理解上的冲突和混乱,为作战仿真系统的开发扫清了道路.     

Ontology的实质是“本体论模型”

为了不改变语义性质和不造成概念冲突,Ontology不能汉译为“本体”。Ontology的“本体论”译名也不利于其在计算机工程领域中的实际应用。Ontology术语是作为本体论思维方式从哲学领域借用的。Ontology就是信息产品背后的、决定其性质的“概念系统”,将其理解为“本体论模型”不仅有方法论依据、语言学依据、模型方法依据,而且与Ontology的Gruber定义相一致。本体论模型是与数学模型、物理学模型并列的研究方法。     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

本体构建的粒计算学习模型

粒计算的核心是粒子、粒层和粒结构。应用粒计算思想和本体论模型定义了本体粒和相容粒概念,给出了计算本体粒集和本体树的生成算法。该算法通过相容类产生初始本体粒集,应用本体粒的内涵分量[IG]扩展其他本体粒,最后联合关系分量[RG]和本体粒的关系构建本体粒集的格分层结构,借助加权树思想生成本体的概念树模型。经过中医喘证本体的实证研究,说明算法正确高效,为本体学习提供了很好的技术途径。     

Human-centered ontology engineering: The HCOME methodology

The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human-Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology. George VOUROS (B.Sc. Ph.D.) holds a B.Sc. in Mathematics, and a Ph.D. in Artificial Intelligence all from the University of Athens, Greece. Currently he is a Professor and Head of the Department of Information and Communication Systems Engineering, University of the Aegean, Greece, Director of the AI Lab and head of the Intelligent and Cooperative Systems Group (InCoSys). He has done research in the areas of Expert Systems, Knowledge management, Collaborative Systems, Ontologies, and Agent-based Systems. His published scientific work includes more than 80 book chapters, journal and national and international conference papers in the above-mentioned themes. He has served as program chair and chair and member of organizing committees of national and international conferences on related topics. Konstantinos KOTIS (B.Sc. Ph.D.) holds a B.Sc. in Computation from the University of Manchester, UK (1995), and a Ph.D. in Information Management from University of the Aegean, Greece (May, 2005). Currently, he is a member of the Intelligent and Cooperative Systems Group (InCoSys) and director of the Information Technology Department of the Prefecture of Samos, Greece. His research and published work concerns Knowledge management, Ontology Engineering and Semantic Web. He has lectured in several IT seminars and has served as member of program committees in international workshops.     

基于本体的MAS黑板模型研究

探讨了基于本体的多智能代理黑板知识库系统(OMSBS)的体系结构及OMABS中Agent的模型、组织和交互方式。提出了一种描述混合知识类型的本体知识表达模型。本体在OMSBS中作为领域知识智能代理的知识库,是知识共享和智能代理之间通讯的基础,设计了一类调度智能代理以控制知识源智能代理的行为。OMSBS可以表达混合类型知识及其推理过程,具有良好的适应性和扩展性,呈现出开放结构。     

MOBMAS: A methodology for ontology-based multi-agent systems development

Ontologies offer significant benefits to multi-agent systems: interoperability, reusability, support for multi-agent system (MAS) development activities (such as system analysis and agent knowledge modeling) and support for MAS operation (such as agent communication and reasoning). This paper presents an ontology-based methodology, MOBMAS, for the analysis and design of multi-agent systems. MOBMAS is the first methodology that explicitly identifies and implements the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In this paper, we present comprehensive documentation and validation of MOBMAS.     

The formal-CAFE methodology and model checking patterns in the specification of e-commerce systems

Electronic commerce is an important application that has evolved significantly recently. However, electronic commerce systems are complex and difficult to be correctly designed. Guaranteeing the correctness of an e-commerce system is not an easy task due to the great amount of scenarios where errors occur, many of them very subtle. In this work we presents a methodology that uses formal-method techniques, specifically symbolic model checking, to design electronic commerce applications and to automatically verify them. Also, a model checking pattern hierarchy has been developed—it specifies patterns to construct and verify the formal model of e-commerce systems. We consider this research the first step to the development of a framework, which will integrate the methodology, an e-commerce specification language based on business rules, and a model checker. Adriano Pereira received the B.S. and M.S. degrees in computer science in 2000 and 2002, respectively, and he is currently pursuing the Ph.D. degree in computer science from the Federal University of Minas Gerais, Belo Horizonte, Brazil. His current interests are on performance analysis and modeling of e-business and distributed systems, and formal methods. Mark Song received the B.S., M.S. and Ph.D. degrees in computer science from the Federal University of Minas Gerais, Belo Horizonte, Brazil. His current interests are on distributed systems and formal methods – especially BMC (Bounded Model Checking). Gustavo Franco received the B.S. and M.S. degrees in computer science in 2001 and 2004, respectively, from the Federal University of Minas Gerais, Belo Horizonte, Brazil. His research was on modeling the user behavior of e-business and distributed systems, and formal methods. Actually his current interests are on software engeneering and project management of IT projects.     

Putting value of information theory into practice: a methodology for building sequential decision support systems

Abstract: The paper presents a methodology for building sequential decision support systems based on decision theory using value of information (for short, DT‐VOI based SDSSs). DT‐VOI based SDSSs support decision‐makers in difficult problems of sequential decision‐making. In particular we consider the problem of building DT‐VOI based SDSSs which are capable of supporting decisions in critical situations where (1) making a decision entails knowing the states of some critical hypotheses, and such knowledge is acquired by performing suitable tests; (2) test outcomes are uncertain; (3) performing a test entails, in general, some drawbacks, so that a trade‐off exists between such drawbacks and the value of the information provided by the test; (4) performing a test has the side‐effect that it changes the expected benefit from performing other tests; (5) exceptional situations alter probability and utility default values.     

TEx-Sys model for building intelligent tutoring systems

Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student’s characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the first time, our approach to research, development and implementation related to intelligent tutoring systems and ITS authoring shells. Our research relies on the traditional intelligent tutoring system, the consideration that teaching is control of learning and principles of good human tutoring in order to develop the Tutor–Expert System model for building intelligent tutoring systems in freely chosen domain knowledge. In this way we can wrap up an ongoing process that has lasted for the previous fifteen years. Prototype tests with the implemented systems have been carried out with students from a primary education to an academic level. Results of those tests are advantageous, according to surveys, and the implemented and deployed software satisfies functionalities and actors’ demands.