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

目前正在使用许多基于规则的系统，主要取决于最初给出的XPERT的规则，没有专家能够准备完美的规则通过手动操作是正确的，本研究的目的是开发系统的校正。在正确的谓词（称为基本谓词）中，不需要修改，谓词（称为规则谓词）作为维护的目标，其身体部分由基本谓词（单个规则可决定的规则基础）描述。 NE…更多的W问题，仅通过将结果分为积极案例和负面案例，以及新的正式Casses，这些案例不是由规则基础得出的，但是正确的。首先，搜索错误的规则R，然后使用togoratem阳性示例从r中获取r的歧视规则D，最后是ds ds ds。好像是针对专家从Casses进行的归纳研究的遗失法规。通过我们自动化对象对象对象的自动化分析SS支撑方法的有效性

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)