On the development of Intelligent CAI system on the Internet

浅谈互联网智能CAI系统的发展

• 批准号: 11555103
• 负责人: HIROTA Kaoru
• 金额: $ 5.44万
• 依托单位: Tokyo Institute of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 1999
• 资助国家: 日本
• 起止时间: 1999 至 2001
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-11555103/
• 关键词: CAI; CISG; Fuzzy Inference; Legal argument; Case-based reasoning; Internet; Legal expert system; 法律エキスパート; 法律エキスパートシステム

A fuzzy legal expert system (FLES) based on similarity measure is constructed as a basis for the computer aided instruction (CAI) in the law field. The target law of the FLES is the United Nations Convention on Contracts for the International Sale of Goods (CISG). The aim of the FLES is to classify vague legal concepts in the CISG and support the education for the beginners of international law.The FLES is composed of fuzzy legal case-based reasoning (FLCBR) module and fuzzy legal argument (FLA) module. The former provides a primary study on vague legal concepts. The latter is the extension of the former, and can make an argument between plaintiff and defendant. The fuzziness and context-sensitive effects are taken into account in the knowledge representation and similarity measures in these two modules. In FLCBR, a hierarchical fuzzy frame is introduced to represent the case that is composed of issues, features and case rules. The similarity measure in the case of retrieval and inference is based on the newly introduced Hausdorff distance-based similarity measure.In FLA, a fuzzy factor hierarchy is studied to represent the case that is composed of issues, abstract factors and atomic factors. The legal argument consisting of claim, objection and rebuttal, that reflect the viewpoints of plaintiff and defendant, is modeled by the factor-based similarity measure that is a structural similarity measure integrated the Hausdorff distance-based similarity, the fuzzy extension of the feature-based similarity and the newly proposed context-based similarity.The constructed system is evaluated by several students in law school, and proved that this research project leads to the realization of CAI system in the law field.

本文提出了一种基于相似性测度的模糊法律的专家系统（FLES），为法律领域的计算机辅助教学（CAI）奠定了基础。FLES的目标法律是《联合国国际销售合同公约》（《销售公约》）。该系统由模糊法律的案例推理（FLCBR）模块和模糊法律的论证（弗拉）模块组成，旨在对CISG中模糊的法律的概念进行分类，为国际法初学者的教学提供支持。前者对模糊法律的概念进行了初步研究。后者是前者的延伸，可以在原告和被告之间进行辩论。这两个模块在知识表示和相似性度量中考虑了模糊性和上下文敏感性的影响。在FLCBR中，引入了一个层次模糊框架来表示由问题、特征和案例规则组成的案例。在检索和推理的情况下，相似性度量是基于新引入的基于Hausdorff距离的相似性度量，在弗拉中，研究了一个模糊的因素层次来表示由问题，抽象因素和原子因素组成的情况。基于因素的相似性度量是一种综合了Hausdorff距离相似性、特征相似性的模糊扩展和新提出的上下文相似性的结构相似性度量方法，该方法对由原告和被告的主张、异议和反驳组成的法律的论证进行了建模，并由法学院的几名学生对构建的系统进行了评价。并证明了本课题的研究成果对法学领域CAI系统的实现具有一定的指导意义。

项目成果

高間康史,Mitsuru Ishizaka: "Fisheye Matching: Viewpoint-Sensitive Feature Generation Based on Concept Structure (Extended Summary)"Al'99, Lecture Notes in Artificial Intelligence. 1747. 465-466 (1999)

Mitsuru Ishizaka：“鱼眼匹配：基于概念结构的视点敏感特征生成（扩展摘要）”Al99，人工智能讲义。1747。465-466（1999）

K.Hirota: "On Similarity Measure for Fuzzy Legal Expert System CISG"6-th Int. Conf. on Soft Computing (IIZUKA2000) (Best Paper Awarded) (Iizuka. Japan). 813-818 (2000)

K.Hirota：“论模糊法律专家系统 CISG 的相似性度量”6-th Int。

K.Hirota, M.Xu, Y.Takama: "On Similarity Measure for Fuzzy Legal Expert System CISG"6-th Int. Conf. on Soft Computing (IIZUKA2000)(Best Paper Awarded)(Iizuka, Japan). 813-818 (2000)

K.Hirota，M.Xu，Y.Takama：“论模糊法律专家系统 CISG 的相似性度量”6-th Int。

K.Hirota, M.Xu, Y.Takama, H.Yoshino: "Implementation of Fussy Legal Expert System FIES"Int. J. of Advanced Computational Intelligence. 421-427 (2001)

K.Hirota、M.Xu、Y.Takama、H.Yoshino：“模糊法律专家系统 FIES 的实施”Int。

広田薫: "A Fuzzy Expert System for CISG.Plenary Speech"8th Int. Fuzzy Systems Association World Congress (IFSA'99). (1999)

Kaoru Hirota：“CISG 的模糊专家系统。全体会议演讲”第 8 届国际模糊系统协会世界大会 (IFSA99) (1999)。