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A Research of machine learning of object oriented analysis knowledge by induvtive reasoning

归纳推理面向对象分析知识的机器学习研究

基本信息

批准号：
09680377
负责人：
HARADA Minoru
金额：
$ 1.92万
依托单位：
Aoyama Gakuin University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 1999
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-09680377/
关键词：
theory revision discrimination rule progol prolog object oriented analysis automation rule base maintenance 帰納学習 progol 帰納推論格フレーム生成オブジェクト指向分析自然語処理

项目摘要

A lot of rule-based systems are presently in use. However, the reliabilities of these systems depend primarily on the rules initially given by the expert on the domain. No expert is capable of preparing a perfect rule base because creating a complete set of rules would require that every possible situation has been considered, Hence, if an incorrect execution result comes out, it is usual to correct the rule base by manual operation. The purpose of the present study is to develop system THERES (Theory Revision System) which automates this correction of rules. The rule base which THERES revises is a Horn clause set described with prolog. The predicates which compose the rule base are assumed to be divided into the correct predicates (called basic predicates) which need not be revised and the predicates (called rule predicates) as the target of maintenance, whose body section is described by basic predicates (single rule decidable rule base). After the rule base system is applied to a ne … More w problem, only by dividing the results into the positive cases and the negative cases and also by pointing out the new positive cases which were not derived by the rule base but are thought to be correct, THERES automatically revises the rule base so as to solve this problem correctly. THERES first searches incorrect rule R, then acquires discrimination rule D derived from R using the inductive learning system Progol to separate positive and negative examples of R, and finally adds the body of D to that of R in the form of a conjunction. The proposed system corrects incorrect rules as if adding missing regulations on exceptions to the existing rules created by an expert. Therefore, it is more practical than to replace the existing rules by the rules acquired by inductive learning from the cases. The present study applies THERES to revise the rule base of an automatic object-oriented analysis system CAMEO, a practical rule base system previously developed by us for automating object oriented analysis, in order to discuss the effectiveness of the proposed method. Less

目前有许多基于规则的系统正在使用。然而，这些系统的可靠性主要取决于规则最初由该领域的专家。没有一个专家能够准备一个完美的规则库，因为创建一个完整的规则集需要考虑到每一种可能的情况，因此，如果出现错误的执行结果，通常需要手动操作来纠正规则库。本研究的目的是开发系统有（理论修订系统），自动化的规则，这种校正。THERES修改的规则库是一个用prolog描述的Horn子句集。假设构成规则库的谓词分为不需要修改的正确谓词（称为基本谓词）和作为维护对象的谓词（称为规则谓词），其主体部分由基本谓词（单规则可判定规则库）描述。将规则库系统应用于一个新的 ...更多信息 w问题，只需将结果分为正例和负例，并指出不是由规则库导出的但被认为是正确的新正例，THERES就能自动修正规则库，从而正确地解决该问题。THREES首先搜索不正确的规则R，然后利用归纳学习系统Progol分离R的正例和反例，得到由R导出的判别规则D，最后将D的主体以合取的形式添加到R的主体中。拟议的制度纠正了不正确的规则，就好像在专家制定的现有规则中增加了缺失的例外规定。因此，它比用从案例中归纳学习得到的规则来代替现有的规则更实用。本研究适用于修改规则库的自动面向对象的分析系统CAMEO，一个实用的规则库系统，我们以前开发的自动面向对象的分析，以讨论所提出的方法的有效性。少

项目成果

期刊论文数量（12）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

原田実、野村佳秀、山本幸二、大野雅志、田村浩樹、高橋史郎: "自然語要求仕様からオブジェクト指向設計図を自動生成するシステムCAMEO"情報処理学会論文誌. 38. 2031-2039 (1997)

Minoru Harada、Yoshihide Nomura、Koji Yamamoto、Masashi Ohno、Hiroki Tamura、Shiro Takahashi：“CAMEO，一种根据自然语言需求规范自动生成面向对象蓝图的系统”日本信息处理学会杂志 38. 2031-2039。 (1997)