基于本体的数字图书馆检索模型研究(Ⅳ)——历史领域知识推理机制

基于本体的领域知识推理主要分为基于逻辑的领域知识检错推理和基于关系的领域蕴涵知识发现推理。对本体描述的领域知识进行推理,可以检测知识逻辑体系错误,减少领域本体构建繁琐的工作量,减轻对领域专家的依赖,发现领域蕴涵知识。在国共合作领域知识进行语义关系分析的基础上,提炼推理规则库,并分别运用TABLEAU算法和RETE模式匹配算法,在推理引擎Racer和Jena中实现了逻辑检错推理和蕴涵知识发现推理。     

语义web环境下语义推理的研究与实现

从语义推理技术入手,主要针对描述逻辑、推理算法和推理机三个方面进行了研究分析。在此基础上,本文进行了语义推理原型系统的设计与实现。系统在语义分析模块中利用语义推理进行检索词的规范和扩展,在语义检索模块通过语义推理挖掘关联隐含知识。通过语义推理原型系统的构建,利用专用推理机Pellet与Jena推理子系统层叠的方式进行语义推理,为今后各种知识服务系统的语义推理提供参考依据。     

Automatic verification of distributed logic specifications

Formal specification is vital to the development of distributed real-time systems as these systems are inherently complex and safety-critical. It is widely acknowledged that formal specification and automatic analysdis of specifications can significantly increase system reliability. Although a number of specification techniques for real-time systems have been reported in the literature, most of these formalisms do not adequately address to the constraints that the aspects of ‘distribution’ and ‘real-time’ impose on specifications. Further, an automatic verification tool is necessary to reduce human errors in the reasoning process. In this regard, this paper is an attempt towards the development of a novel executable specification language for distributed real-time systems. First, we give a precise characterization of the syntax and semantics of DL. Subsequently, we discuss the problems of model checking, automatic verification of satisfiability of DL specifications, and testing conformance of event traces with DL specifications. Effective solutions to these problems are presented as extensions to the classical first-order tableau algorithm. The use of the proposed framework is illustrated by specifying a sample problem.     

Acquisition and validation of software requirements

This paper presents a knowledge-based software engineering tool, DASERT (Detection of Anomalies in Software Engineering Requirements Texts), to acquire and validate functional requirements in natural language. The user describes the functional specifications through informal methods, using graphics with comments in natural language. During this elaboration step the system validates the document by processing the comments semantically to detect ambiguities or inconsistencies. To do so it uses natural language processing and knowledge base engineering.DASERT's kernel is a KL-ONE-like semantic network, which helps the semantic parsing of the comments and their semantic representation. This knowledge base is first initialized by the acquisition of the lexical domain knowledge, then progressively enriched with the domain terminology given by the user and with the requirements knowledge extracted from the user's graphics and texts.During initialization and enrichment, the network manager validates the knowledge structurally. This ensures the logical consistency of the base which is then checked for inconsistencies and ambiguities specific to the domain of software requirements.From a software engineering point of view, the originality of DASERT is that it provides a semantic checking of an informal specification by interpreting the natural language comments. From a knowledge acquisition point of view, DASERT allows acquisition from texts to build the kernel of a knowledge base which is then used to guide the semantic parsing of texts during the acquisition of the specification itself. Moreover, the representation formalism provides a unified view of acquisition and validation.     

基于本体的题名自动分类研究

本文依据中国知网、《中图法》、《中国分类主题词表》等知识库,通过对领域词语的概念化处理、建立推理规则、过滤掉阈值较低的词语等手段,形成领域词语本体知识库;然后,根据待分类题名的语义逻辑关系,结合基于距离的语义相似度的计算规则,形成一种应用于领域词语本体的题名自动分类方法,该方法在一定程度上弥补了文献题名特征不足的缺点,且提高了准确率和召回率。     

基于语义的数字图书馆推理检索研究

传统数字图书馆检索技术处理语义能力弱。为此,应运用本体的思想和方法组织数字图书馆资源,在资源内容描述语义形式化中引入规则推理技术,把检索从基于关键词匹配层提高到基于语义的知识推理层面。图1。参考文献9。     

知识组织系统构建中对既有资源的利用方式分析

知识组织系统的构建是一项艰巨而复杂的工作,而利用既有资源,尤其是词表和语料,则在一定程度上能够减少这一任务的工作量。文章据此研究了对既有资源利用方式的四个相关问题。首先是从既有知识组织系统中提取出所需局部的方式及注意事项。其次是跨语言利用外文知识组织系统,生成当地语言知识组织系统雏形。再次是从选词、相关词推荐和词间关系验证等角度分析语料库在知识组织系统构建过程中的应用。最后探索了建设中的知识组织系统的利用方式,并提出了两个循环模型。了解和掌握对既有资源的利用方式,能够促进更好更快地构建知识组织系统。     

Dipe-D: A Tool for Knowledge-Based Query Formulation in Information Retrieval

The paper reports the development of Dipe-D, a knowledge-based procedure for the formulation of Boolean queries in information retrieval. Dipe-D creates a query in two steps: (1) the user's information need is developed interactively, while identifying the concepts of the information need, and subsequently (2) the collection of concepts identified is automatically transformed into a Boolean query. In the first step, the subject area—as represented in a knowledge base—is explored by the user. He does this by means of specifying the (concepts that meet his) information need in an artificial language and looking through the solution as provided by the computer. The specification language allows one to specify concepts by their features, both in precise terms as well as vaguely. By repeating the process of specifying the information need and exploring the resulting concepts, the user may precisely single out the concepts that describe his information need. In the second step, the program provides the designations (and variants) for the concepts identified, and connects them by appropriate operators. Dipe-D is meant to improve on existing procedures that identify the concepts less systematically, create a query manually, and then sometimes expand that query. Experiments are reported on each of the two steps; they indicate that the first step identifies only but not all the relevant concepts, and the second step performs (at least) as good as human beings do.     

本体在汉英机器翻译中的应用研究

介绍本体作为知识工程领域的一种新方法被引入到汉英机器翻译的研究中,用来协助机器翻译中对自然语言语义的理解和计算;指出本体为源语言与目标语言的词汇提供中性化、形式化的表达,其概念语义网络为自然语言的歧义消除提供世界知识、语义空间,本体工具本身所具有的推理功能也使机器翻译的语义处理更为便捷,本体已逐渐成为语义处理的新的理论基础及工具。     

自然语言语义分析研究进展

按照自然语言的构成层次——词语、句子和篇章,分析各层次语义分析的内涵、现有的研究策略、理论依据及存在的主要方法,并对现存的两类主要研究策略进行对比分析.认为词语语义分析是指确定词语意义,衡量两个词之间的语义相似度或相关度;句子语义分析研究包含句义分析和句义相似度分析两方面;文本语义分析就是识别文本的意义、主题、类别等语义信息的过程.当前的自然语言语义分析主要存在两种主要的研究策略:基于知识或语义学规则的语义分析和基于统计学的语义分析.基于统计与规则相融合的语义分析方法是未来自然语言语义分析的主流方法,本体语义学是自然语言语义分析的重要基础.     

结合本体考察情报语言学的发展

从本体的概念、知识组织系统层次、本体的编制方法及其在信息检索系统领域的应用等角度,分析本体与情报检索语言之间的联系。结合本体的特点,指出情报语言学的发展趋势是语义性加强;使用主体范围扩大;“透明化”加强;共享和兼容等。     

从信息构建看未来的知识管理

本文从信息构建出发 ,进而引申到知识管理与知识推理 ,最终提出了知识基础工程。在设计并实现自然语言的语法开发平台时 ,产生了构建知识库的设想。利用语法开发平台 ,就可以对自然语言的语法进行开发 ,加上一个好的算法 ,就可以对大规模文本进行自动分析。对分析过的句子进行内容提取 ,并用面向对象方法和逻辑形式进行格式化 ,得到以面向对象为特征的常识知识库和以逻辑命题为特征的专家知识库 ,这应该是知识发现、知识管理的最高层次 ,也是知识工程的核心     

Acquiring first-order knowledge about air traffic control

This paper presents an application of knowledge intensive generalization to knowledge acquisition, in the domain of air traffic control. We explain why knowledge intensiveness and first-order logic are sometimes necessary, as for instance in the application field studied here. An obvious advantage of first-order logic is its power of expression, while an obvious drawback is long computation time. We also describe some less obvious advantages and drawbacks of first-order logic, especially when the knowledge must be expressed as Horn clauses to retain some computational efficiency. Finally, we emphasize the large translation problem that must be solved in order to allow an efficient interaction with the expert. Two translation phases are necessary. One goes from the expert's language to Horn clauses, the second one goes back from Horn clauses to the expert's language. The first one is necessary to ensure automatic learning, while the second one allows the expert to understand what has been learned. Both phases are far from trivial and ask for choices that must be made carefully in order to avoid losing significant information. One of our unexpected results is that the second translation phase plays the role of a validation step. It thus becomes a very efficient way to acquire knowledge the expert has problems formalizing. Using first-order logic does complicate things, but it provides, as a reward, a powerful way of extracting and validating the acquired knowledge, especially when the field expert is unable to express his knowledge in a simple way.     

基于数字图书馆的本体演化和知识管理研究(Ⅰ)——本体分子理论

语义网中的一个核心技术就是本体及其推理机制,随着语义网技术的发展,本体在各个领域得到了广泛的应用.本体在数字图书馆提供了一种全新的知识管理模式,较好地解决了知识组织、知识检索等问题.但是目前基于本体的知识管理仅仅局限于静态知识和绝对知识,对于知识的真实性、权威性这些问题也还没有明确的解决方案.本文针对本体实现动态知识管理与控制存在的不足,作者提出了本体分子理论.文章从理论的提出、理论的形式化描述进行了充分论证,论述了分子的核子是本体不可变的属性,离子是可变的属性,只要核子相同就同属一个本体.文章以知识管理为例,详细分析了动态知识演化过程和控制管理.     

基于Web的情报知识元挖掘与语义集成地图

Web广泛使用的信息组织与表示语言HTML将显示方式内嵌在数据中,这使得应用程序很难将内容与显示方式分离开来.本文提出一个基于网页信息的知识元挖掘方法,通过汉语分词、词性标注预处理,用软件实现了具有三元组语义关系的知识元结构的挖掘,利用 Protégé本体开发工具实现了基于知识元集成的军事情报语义网地图.试验表明,这是一种快速获取情报知识元的有效方法.     

逻辑学原理在基于本体的知识组织中的应用

在介绍本体论和逻辑学基本原理的基础上,分别从概念逻辑、思维逻辑、谓词逻辑和归纳推理逻辑四个方面探讨了逻辑学原理在本体构建方法、本体检错推理和本体整合技术三方面基于本体的知识组织中的应用。     

(ML)2: A formal language for KADS models of expertise

This paper reports on an investigation into a formal language for specifying KADS models of expertise. After arguing the need for and the use of such formal representations, we discuss each of the layers of a KADS model of expertise in the subsequent sections, and define the formal constructions that we use to represent the KADS entities at every layer: order-sorted logic at the domain layer, meta-logic at the inference layer and dynamic-logic at the task layer. All these constructions together make up (ML)², the language that we use to represent models of expertise. We illustrate the use of (ML)² in a small example model. We conclude by describing our experience to date with constructing such formal models in (ML)², and by discussing some open problems that remain for future work.     

从RDF(S)到OWL,什么在改变之中?

作为一种Ontology描述语言，需要具有丰富的语义表达能力、精确的语义表述性能和有效的可计算性。鉴于RDFS语义表达能力的有限，OWL借鉴了DAML，OIL和DAML OIL的经验，在RDFS的基础之上，通过增加语言构成要素，扩充了RDFS的语义表达能力，并且提高了语义表述的精确性，然而随之而来的是计算复杂性和推理难度的增加，有效可计算性的降低。描述逻辑的存在为OWL语言的设计打下了重要的基础，使OWL能够在表达能力和可计算性之间找到平衡。     

面向知识处理的领域本体及其应用研究

本体是关于领域概念及概念之间关系的精确描述。本文给出面向知识处理的领域本体模型及其描述语言。一个本体由实例、类、属性、关系和类间关系等元素组成。在给出领域知识本体模型的基础上,给出了基于框架的领域知识本体表示语言、三层组织结构以及本体的公理体系。在领域本体的驱动下,以数学家知识获取为例给出一种面向领域的知识获取方法,并给出领域知识语义正确性检查的方法。最后介绍一个领域本体管理和知识获取工具。     

基于数字图书馆的本体应用环境研究

语义Web框架虽已提出多年,但大部分应用都只是系统模型,很少投入实际的商业运作.为此,笔者从实用的角度提出本体应用环境的概念与框架.本体应用环境以本体技术为核心,以知识管理为目标,较好地解决了各领域知识管理中的各种问题,如知识组织、知识检索和知识推理等.目前,本体应用环境已经成功应用于数字图书馆、数字档案馆等领域,为语义Web的发展提供了一种可行的思路.