근사질의응답기능을 이용한 협동적 사례기반추론 = Cooperative Case-based Reasoning Using Approximate Query Anwering

다국어 초록 (Multilingual Abstract)

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure
Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information.
Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

목차 (Table of Contents)

• Ⅰ. 서 론
• Ⅱ. 협동적 응답기능으로서의 AQA
• 2.1 엄밀질의응답기능과 협동적 응답기능으로서의 AQA 비교
• 2.2 유사성의 제측면
• 2.3 인접응답집합 결정을 위한 추상화 계층구조
• Ⅲ. 협동적 응답기능을 이용한 CBR의 추론과정
• 3.1 AQA를 이용한 CBR의 추론과정
• 3.2 유사성개념을 이용한 선호 휴리스틱기법
• 3.3 적용예
• Ⅳ. 결 론
• 참고문헌
• Abstract