基于本体的法律知识库的研究与实现

基于描述逻辑的本体理论已广泛用于知识表示和推理，而本体在法律领域的研究和应用在国外已开展近10年，目前国内、还没有这方面的研究与应用成果。本文研究分析了国内外法律知识库的成果，结合中国的法律法规给出了一个法律领域的本体模型DOLegal，介绍了法律知识库的设计思路及架构。在知识库原型中加入了国内部分法规涉及的行为及处罚，实现了法律知识的表示和推理。文中还对设计中遇到的一些难点进行了研究与分析。     

基于框架与规则相结合的棉纺工艺专家系统知识库的设计

本文讨论了棉纺工艺专家系统及其知识表示方法。在介绍棉纺工艺专家系统体系结构的基础之上，重点探讨了利用框架表示棉纺工艺的领域知识的具体方法、框架结构以及用框架一规则形式来表示推理规则及原理。并简要介绍了本系统基于事例的推理过程。     

异常解释专家系统中的知识库模型

本文从领域专家解释异常的过程出发，分析了领域知识及推理解释的过程。给出了相应的知识表示方法和知识库模型。实践表明这种知识表示方法及知识库模型，具有较高的效率，对建造异常解释类专家系统具有指导意义。     

基于专家系统技术的网络计划工期估算研究

本文主要探讨了专家系统技术在网络计划工作估算中的应用.首先分析了网络计划的领域知识,并采用面向对象的方法进行知识表示;在推理机制中讨论了在面向对象知识表示情况下的推理流程.最后对ESDENP的结构和主要功能作了介绍.     

OWL DL的形式化基础研究

W3C正在制定的OWL DL是一种面向语义Web的知识表示标记语言，具有较强的知识表达能力并适合大规模应用的推理效率，是语义Web领域对适合语义Web应用的知识表示标记语言进行研究的最新综合．在知识表示领域，为了对知识表达能力和推理效率做合适的折衷，进行了大量关于描述逻辑的研究，本文以描述逻辑作为OWL DL的形式化基础，详细分析了OWL DL和描述逻辑间的对应关系，用描述逻辑的语义解释了OWL DL的各个基本元素，从而可以将描述逻辑领域研究的大量成果应用到OWL DL上来，为进一步研究OWL DL的知识表示、推理等问题奠定了基础．     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

域规则表示和主线推理法

传统的产生式知识表示，在规则式中没能体现出前提对结论的影响程度和结论间的相互关系，而这在许多领域中是存在的。基于产生式表示的专家系统，其推进算法是顺序的，而且在推理过程中不作任何判断，这大大影响了系统的推理速度，本文提出了影响率和域规则知识表示等概念及一种新的推理算法。     

基于集成式知识表示的专家系统开发工具

本文针对工程应用中知识的特点，提出了一种新型的知识表示方法－集成式的知识表示，给出了这种知识表示的ＢＮＦ范式，并就如何这诸多类型的知识正确、高效地推理进行了详细读者论坛，同时给出了推理过程的算法。     

DBEST：一个实用的故障诊断专家系统开发工具

本文介绍了一个基于故障诊断领域的专家系统开发工具ＤＢＥＳＴ的设计与实现。它在Ｗｉｎｄｏｗｓ环境下将多种知识表示方法和多种故障推理策略融为一体，是快速高效开发实用故障诊断专家系统的强有力的工具。文中着重介绍了模糊关系矩阵的知识表示，知识获取和推理方法。     

基于本体的应急救援知识库构建及其应用

针对专家系统在应急救援领域应用中存在的知识表示及推理等问题,采用基于本体的知识表示方法与基于Jena的规则推理引擎,参考简单知识工程方法论与Jena规则语法建立一个高速公路应急救援本体与推理规则,实现本体知识库的推理。将该知识库应用于高速公路应急救援系统中,结果表明其具备解决实际问题的能力;有利于领域知识的共享与重用;促进了专家系统在高速公路应急救援领域的发展。     

A principled approach to developing legal knowledge systems

In this article we present a principled, four-phased approach to the development of legal knowledge systems. We set out from the well-studied CommonKADS method for the development of knowledge systems and tailor this method to the legal domain. In particular, we propose a generic legal ontology, and describe the creation of statute-specific ontologies to adopt the method for building legal systems. In the construction of these ontologies, we start from a theoretical analysis of the legal domain. The well-known example of the Imperial College Library Regulations (ICLR) is used to illustrate the method.     

Knowledge Criteria for the Evaluation of Legal Beliefs

In this article, we describe an evaluation framework for legal information systems. The framework is based on knowledge criteria. We distinguish four belief types, i.e. perceptual beliefs, testimonial beliefs, inferential beliefs, and interpretative beliefs. Beliefs of these types can be transformed into knowledge by the fulfilment of knowledge criteria. The knowledge criteria examined are truth, proper justification, reliability, consistency, and coherence. There is a hierarchy among these criteria. We will show that beliefs, depending on the type they belong to, become knowledge by applying different subsets of these criteria. Two legal information systems are evaluated using this framework. Results are presented and two conclusions are drawn. Finally, further research on legal knowledge criteria is suggested.     

面向法律文书的自然语言理解

法律人工智能因其高效、便捷的特点,近年来受到社会各界的广泛关注。法律文书是法律在社会生活中最常见的表现形式,应用自然语言理解方法智能地处理法律文书内容是一个重要的研究和应用方向。该文梳理与总结面向法律文书的自然语言理解技术,首先介绍了五类面向法律文书的自然语言理解任务形式: 法律文书信息提取、类案检索、司法问答、法律文书摘要和判决预测。然后,该文探讨了运用现有自然语言理解技术应对法律文书理解的主要挑战,指出需要解决好法律文书与日常生活语言之间的表述差异性、建模好法律文书中特有的推理与论辩结构,并且需要将法条、推理模式等法律知识融入自然语言理解模型。     

Ontologies of Professional Legal Knowledge as the Basis for Intelligent IT Support for Judges

In this paper, we describe the use of legal ontologies as a basis to improve IT support for professional judges. As opposed to most legal ontologies designed so far, which are mostly based on dogmatic and normative knowledge, we emphasize the importance of professional knowledge and experience as an important pillar for constructing the ontology. We describe an intelligent FAQ system for junior judges that intensively use the ontology.     

From a rule-based conception to dynamic patterns. Analyzing the self-organization of legal systems

The representation of knowledge in the law has basically followed a rule-based logical-symbolic paradigm. This paper aims to show how the modeling of legal knowledge can be re-examined using connectionist models, from the perspective of the theory of the dynamics of unstable systems and chaos. We begin by showing the nature of the paradigm shift from a rule-based approach to one based on dynamic structures and by discussing how this would translate into the field of theory of law. In order to show the full potential of this new approach, we start from an experiment with NEUROLEX, in which a neural network was used to model a corpus of French Council of State decisions. We examine the implications of this experiment, especially those concerning the limits of the model used, and show that other connectionist models might correspond more adequately to the nature of legal knowledge. Finally, we propose another neural model which could show not only the rules which emerge from legal qualification (NEUROLEX's goal), but also the way in which a legal qualification process evolves from one concept to another.     

Brussels revisited: The European conflicts guide

In this paper, we examine the soundness of Capper & Susskind's recommended legal expert system development methodology in the areas of knowledge acquisition and knowledge representation. Legal expert systems have not yet had the impact in the United Kingdom that might be expected. We argue that this is partly the result of developers paying insufficient attention to the ‘third estate’: user interfaces. We make suggestions about both the look and feel of legal expert systems, and the facilities that such systems should offer. Lastly, we claim that we have developed an exploratory expert system encapsulating the Brussels Convention 1968 which can contribute to the development of a useful computer‐based guide to an important legal domain.     

Legal modeling and automated reasoning with ON-LINE

In this paper we present a modeling approach to legal knowledge systems and its computational realization in the ON-LINE architecture. ON-LINE has modules for modeling legal sources, for storing and retrieving legal information and for reasoning with legal knowledge. The approach takes two perspectives: domain and task. In the domain perspective, a core ontology divides legal knowledge into five major categories: normative, world, responsibility, reactive and creative. For the normative knowledge, which is most typical of legal domains, we developed a new representation and inference formalisms which are an alternative to deontic logic. For the world knowledge, we argue for using a terminological knowledge representation language. The structure of the ontology is not a taxonomy, but a network of dependencies between the categories. These dependencies reflect the global structure of arguments in legal reasoning. In the task perspective, we followed a top-down approach using the CommonKADS modeling library. Design, planning and assessment were identified as typical tasks in the legal domain. For assessment, a model was specified and implemented.     

BankXX: Supporting legal arguments through heuristic retrieval

The BankXX system models the process of perusing and gathering information for argument as a heuristic best-first search for relevant cases, theories, and other domain-specific information. As BankXX searches its heterogeneous and highly interconnected network of domain knowledge, information is incrementally analyzed and amalgamated into a dozen desirable ingredients for argument (called argument pieces), such as citations to cases, applications of legal theories, and references to prototypical factual scenarios. At the conclusion of the search, BankXX outputs the set of argument pieces filled with harvested material relevant to the input problem situation.This research explores the appropriateness of the search paradigm as a framework for harvesting and mining information needed to make legal arguments. In this article, we describe how legal research fits the heuristic search framework and detail how this model is used in BankXX. We describe the BankXX program with emphasis on its representation of legal knowledge and legal argument. We describe the heuristic search mechanism and evaluation functions that drive the program. We give an extended example of the processing of BankXX on the facts of an actual legal case in BankXX's application domain — the good faith question of Chapter 13 personal bankruptcy law. We discuss closely related research on legal knowledge representation and retrieval and the use of search for case retrieval or tasks related to argument creation. Finally we review what we believe are the contributions of this research to the understanding of the diverse disciplines it addresses.This research was supported in part by grant No. 90-0359 from the Air Force Office of Sponsored Research and NSF grant No. EEC-9209623 State/University/Industry Cooperative Research on Intelligent Information Retrieval.     

Legal Ontologies in Knowledge Engineering and Information Management

In this article we describe two core ontologies of law that specify knowledge that is common to all domains of law. The first one, FOLaw describes and explains dependencies between types of knowledge in legal reasoning; the second one, LRI-Core ontology, captures the main concepts in legal information processing. Although FOLaw has shown to be of high practical value in various applied European ICT projects, its reuse is rather limited as it is rather concerned with the structure of legal reasoning than with legal knowledge itself: as many other “legal core ontologies”, FOLaw is therefore rather an epistemological framework than an ontology. Therefore, we also developed LRI-Core. As we argue here that legal knowledge is based to a large extend on common-sense knowledge, LRI-Core is particularly inspired by research on abstract common-sense concepts. The main categories of LRI-Core are: physical, mental and abstract concepts. Roles cover in particular social worlds. Another special category are occurrences; terms that denote events and situations. We illustrate the use of LRI-Core with an ontology for Dutch criminal law, developed in the e-Court European project.     

A Comparison of Four Ontologies for the Design of Legal Knowledge Systems

There is a growing interest in how people conceptualise the legal domain for the purpose of legal knowledge systems. In this paper we discuss four such conceptualisations (referred to as ontologies): McCarty's language for legal discourse, Stamper's norma formalism, Valente's functional ontology of law, and the ontology of Van Kralingen and Visser. We present criteria for a comparison of the ontologies and discuss the strengths and weaknesses of the ontologies in relation to these criteria. Moreover, we critically review the criteria.