面向业务问题求解的知识资源特定领域建模方法

针对企业中解决业务问题时知识资源利用不合理的问题,提出一种面向业务问题求解的知识资源特定领域模型。首先从领域纲要出发,将业务问题求解领域的基本元素描述出来,并详细分析其中对象之间的关系;然后通过在领域模板中建立的问题-知识事件驱动过程链(PK-EPC)模型对问题求解的流程进行格式化,并匹配到相应的知识单元;其次是通过对应的应用模型对业务问题进行分解,并将前面的知识单元与知识载体匹配。根据前面的模型可得出可供企业选择的集成业务活动、知识单元和知识载体的多层次求解方案模型,为企业业务问题求解提供了快捷准确的方法。最后基于Java设计了面向业务问题求解的企业求解方案建模系统,通过实例验证了该模型的可行性。     

面向事件处置的信息服务集成调度模型

以电子政务、电子商务等城市应用为背景,针对这些应用中跨领域事件处置所涉及的异构、分布式资源、服务集成调度以及跨领域知识共享问题,提出了一个面向事件处置的、基于规则的信息服务集成调度模型.该集成调度模型具有4个分层结构,包括资源层(resource layer)、知识层(knowledge layer)、业务层(business layer)和表示层(representation layer).重点就知识层形式化业务规则的定义、资源和服务的引用以及规则引擎等给出了详细的设计和实现.最后,对该模型进行了验证,实现了一个城市应急联动应用中的统一接警事件处置原型系统.     

基于工作流的知识流建模与控制

知识在多个参与者之间的产生、传播与应用称为知识流.在知识密集型组织中,对业务过程的控制和对知识资产的管理具有紧密的依赖关系.工作流管理是实现业务过程控制的重要技术.当前的工作流过程元模型不支持对知识管理机制的表示.为此,提出了一个扩展的工作流过程元模型,以支持业务过程控制与知识管理的集成.在此基础上,对知识流的建模与控制进行了深入的研究.提出了一种知识流建模方法,通过5类知识流单元对知识传递与重用、人员协作与交流进行表示.针对知识流中的动态因素,研究了基于资源约束、知识需求变化和时间约束的知识流控制方法,以实现自适应的知识流控制,并给出了有关算法.为工作流技术与知识管理技术的有效结合提供了一个有益的途径.     

面向业务的E-维护知识供应模型

为使E-维护中的知识支持维护任务,提出面向业务的知识供应模型。采用维护知识概念本体规范任务描述、维护对象和知识功能,通过知识对象本体集成知识资源。将知识供应的需求和权限集成到业务过程中,构建维护知识供应信息模型,建立知识匹配方法控制知识供应。在某石化企业E-维护平台上的应用结果表明,该模型能提升企业的维护水平。     

主动式知识获取模型

主动式知识获取模型由一套实现机制和一组评估标准组成，实现机制由分类系统、专家推荐系统、文章推荐系统、用户等级评估系统、文章等级评估系统组成。评估标准包括文章评估标准、用户评估标准。该模型的目的是根据用户的情况为用户推荐合适的技术专家和相关的高质量的技术文章，是知识管理方面的一个重要应用。     

面向知识服务的科技资源协同创新服务机制

在对知识即服务元模型进行定义与分析的基础上,提出了一个科技资源协同服务元模型STRCS,该模型包括科技资源模型、服务模型、协同模型3个子模型以及相应的科技资源与服务。同时,通过建立KAAS元模型与科技资源服务元模型间的映射机制,为科技资源平台中的知识服务模式提供了服务映射机制。在此基础上,进一步提出了一种面向KAAS的科技资源协同服务分类与知识聚合新机制,并针对动态多标签和动态文档索引的分类和聚合方式提出了优化的机制,以及科技资源的个性化服务与科技资源的知识协同机制;通过开发实现了一个基于社会化与知识服务化的科技资源公共服务平台,并利用算法优化提升了科技资源平台个性化推荐的能力与精确度,从而为解决科技资源协同创新和个性化知识服务的实施与集成提供了一个新方案。     

基于知识的零样本视觉识别综述

零样本学习旨在通过运用已学到的已知类知识去认知未知类.近年来,“数据+知识驱动”已经成为当下的新潮流,而在计算机视觉领域内的零样本任务中,“知识”本身却缺乏统一明确的定义.本文针对这种情况,尝试从知识的角度出发,梳理了本领域内“知识”这一概念所覆盖的范畴,共划分为初级知识、抽象知识以及外部知识.基于前面对知识的定义和划分梳理了当前的零样本学习（主要是图像分类任务的模型）工作,分为基于初级知识的零样本模型、基于抽象知识的零样本模型以及引入外部知识的零样本模型.本文还对领域内存在的域偏移和枢纽点问题进行了阐述,并基于问题对现有工作进行了总结归纳.最后总结了目前常用的图像分类任务的数据集和知识库,图像分类实验评估标准以及代表性的模型实验结果;并对未来工作进行了展望.     

一种基于粗糙集的诊断型知识发现方法

知识获取是开发专家系统的瓶颈，传统的病害知识获取通常需要一个较长的过程．针对这一问题，本文给出了粗糙集理论和基于规则的作物病害知识之间的关系，即在油菜植病专家知识获取过程中的应用，建立了基于RHINOS 诊断模型的油菜病害的排除规则、包含规则和病害映像，阐述了可能性规则定义，并给出了基于规则描述的自动归纳推理方法，包括全搜索过程、后处理过程、统计测试的评估以及交叉验证和鞋带方法等．实验结果表明，粗糙集不仅是一个很好的知识获取的框架，而且能正确的归纳推理植物病害的规则．这对诊断型专家系统的开发可起到一个很好的辅助作用，在智能化农业信息系统中有着广泛的应用前景．     

面向业务问题求解的知识供应过程模型

为了满足企业在业务问题求解方面的实际需求,提出了一个面向业务问题求解的知识供应过程模型。该模型提出了知识供应过程中的问题空间、知识空间和流程空间的概念及其关联关系,并进一步给出了包含知识的获取、评价、存储和重用的知识供应过程的有关算法。该模型与算法将业务问题求解过程与知识供应过程进行了融合,通过关联关系实现了知识的主动供应,在优化了业务问题求解过程的同时,提高了知识积累的质量和知识重用的效率。基于该模型建立了知识管理问题求解的原型系统KMPSS,并得到了初步应用验证。     

一种以领域知识为中心的知识发现过程模型

针对知识发现在实际应用中的问题,提出了一种以领域知识为中心的知识发现过程模型,并将其形式化,描述了其动态语义。与已有的知识发现过程模型相比,此过程模型更能体现知识发现过程的本质特性,同时具有严格的形式化基础,为知识发现系统的设计和实际的知识发现应用提供了一个新的参考。     

知识编译研究

知识编译是处理命题逻辑知识库常用的一种新技术,知识编译的过程就是把知识转换成易于推理的表示形式.作为一种有效的推理机制,这种技术已经被广泛地应用到各种各样的人工智能领域中.对目前知识编译的研究与应用进行了综述性的介绍,并且从简洁性、多项式时间内支持的查询操作以及多项式时间内支持的转换操作3个方面对各种知识编译目标语言做了系统的阐述.     

Demand-driven knowledge acquisition method for enhancing domain ontology integrity

Knowledge, as the most important resource for the knowledge economy in the 21st century, is fundamental to enterprise competitive strength. Therefore, how to effectively integrate internal and external knowledge and provide correct knowledge to the right users in a timely fashion have become key success factors in business operation.     

Network optimization in supply chain: A KBGA approach

In this paper, we present a Knowledge Based Genetic Algorithm (KBGA) for the network optimization of Supply Chain (SC). The proposed algorithm integrates the knowledge base for generating the initial population, selecting the individuals for reproduction and reproducing new individuals. From the literature, it has been seen that simple genetic-algorithm-based heuristics for this problem lead to and large number of generations. This paper extends the simple genetic algorithm (SGA) and proposes a new methodology to handle a complex variety of variables in a typical SC problem. To achieve this aim, three new genetic operators—knowledge based: initialization, selection, crossover, and mutation are introduced. The methodology developed here helps to improve the performance of classical GA by obtaining the results in fewer generations. To show the efficacy of the algorithm, KBGA also tested on the numerical example which is taken from the literature. It has also been tested on more complex problems.     

Information technology and knowledge in software development teams: The role of project uncertainty

Knowledge is a strategic resource; information technology (IT) is presumed to facilitate its movement among organizational members. The relevant literature, however, is inconclusive. This study reports the results of the effect of IT on knowledge-sharing processes, i.e., knowledge exchange and knowledge combination, under conditions of project uncertainty. Our results indicate that both exchange and combination are necessary to fully explain the relationships and that the consideration of a project's outcome is also important. While project uncertainty confounds the knowledge-sharing processes regardless of technology, the frequency of technology use routinely increases knowledge exchange and combination in a software team.     

Visualising a knowledge mapping of information systems investment evaluation

Information systems (IS) facilitate organisations to increase responsiveness and reduce the costs of their supply chain. This paper seeks to make a contribution through exploring and visualising knowledge mapping from the perspective of IS investment evaluation. The evaluation of IS is regarded as a challenging and complex process, which becomes even more difficult with the increased complexity of IS. The intricacy of IS evaluation, however, is due to numerous interrelated factors (e.g. costs, benefits and risks) that have human or organisational dimensions. With this in mind, there appears to be an increasing need to assess investment decision-making processes, to better understand the often far-reaching implications associated with technology adoption and interrelated knowledge components (KC). Through the identification and extrapolation of key learning issues from the literature and empirical findings, organisations can better improve their business processes and thereby their effectiveness and efficiency, while preventing others from making costly oversights that may not necessarily be only financial. In seeking to enlighten the often obscure evaluation of IS investments, this paper attempts to inductively emphasise the dissemination of knowledge and learning through the application of a fuzzy Expert System (ES) based knowledge mapping technique (i.e. Fuzzy Cognitive Map [FCM]). The rationale for exploring knowledge and IS investment evaluation is that a knowledge map will materialise for others to exploit during their specific technology evaluation. This is realised through conceptualising the explicit and tacit investment drivers. Among the several findings drawn from this research, the key resulting knowledge mapping through FCM demonstrated the complex, multifaceted and emergent behaviour of causal relationships within the knowledge area. The principal relationships and knowledge within IS investment evaluation are illustrated as being determined by a blend of managerial and user perspectives.     

基于智能主体的决策资源管理

随着Internet的广泛普及,人们可以随时随地获取自己想要的信息,然而海量信息却带来了一场新的知识危机,也就是说,人们被知识的海洋所淹没。知识管理技术正是解决这种知识危机的重要而有效的手段,是知识工程和信息系统中的重要研究内容。论文介绍了该技术在决策资源管理中的应用,提出了一个基于智能主体的决策支持系统的体系结构,并且详细描述了基于本体与RDF的决策资源的知识表示,最后用一个实例阐述了这种决策资源管理方法的实现过程。     

A collaborative platform for cognitive decision making in the Knowledge Society

Two key aspects of the Knowledge Society are the interconnection between the actors involved in the decision making processes and the importance of the human factor, particularly the citizen’s continuous learning and education. This paper presents a new module devoted to knowledge extraction and diffusion that has been incorporated into a previously developed decision making tool concerning the Internet and related with the multicriteria selection of a discrete number of alternatives (PRIOR-Web). Quantitative and qualitative procedures using data and text mining methods have been employed in the extraction of knowledge. Graphical visualisation tools have been incorporated in the diffusion stage of the methodological approach suggested when dealing with decision making in the Knowledge Society. The resulting collaborative platform is being used as the methodological support for the cognitive democracy known as e-cognocracy.     

Semantic Web: A road to the knowledge infrastructure on the internet

In this article, I describe the basic technologies for Semantic Web and relationship between Semantic Web and Knowledge Representation in Artificial Intelligence. Semantic Web is planned as an extension of the current web in order to help cooperation between computers and humans, i.e., computers and humans are expected to understand each other in the knowledge level. I first describe the vision of the Semantic Web, then introduce the current Semantic Web technologies, i.e., RDF, RDFS, and OWL. I describe relationship between the trend of Semantic Web and Knowledge Representation, and clarify challenges and difficulties of Semantic Web from the point of view of Knowledge Representation. Hideaki Takeda: He is a professor at National Institute of Informatics (NII) and a professor in Department of Informatics at the Graduate University of Advanced Studies (Sokendai). He received his Ph.D. from the University of Tokyo in 1991. His research interest in computer science includes ontology engineering, community informatics and knowledge sharing systems.     

智能网络管理中一种基于Petri网的知识验证技术

知识库是智能网络管理系统中的重要组成部分,知识库的维护要求知识库系统必须具备知识的验证功能。智能网管系统中知识组织的动态性决定了知识的结构性验证必须正确、有效和及时。本文以有色Petri网为基础,针对智能网管系统中知识验证的主要内窝,以一种扩充的有色Petri网作为描述和分析工具,建立了相应的知识表示模型和知识验证模型,提出了一种简洁的、基于有色Petri网的知识验证方法,并给出了相应的判定准则。     

Development of a knowledge management initiative and system: A case study

As knowledge emerges as the primary strategic resource in the 21st century, many firms in the manufacturing and service sectors alike are beginning to introduce and implement Knowledge Management (KM). Organisations can certainly benefit from its application for enhanced decision support, efficiency and innovation, thus helping them to realise their strategic mission. However, KM is an emerging paradigm, and not many organisations have a clear idea of how to proceed with it. This paper presents the results of a case study conducted in one company in the United Kingdom (UK), the major aim being to identify how it has developed a KM initiative and system. Hopefully, the information extracted from this study will be beneficial to other organisations that are attempting to implement KM or to those that are in the throes of adopting it.