Generalized case-based reasoning system for portfolio management

摘要

A case-based reasoning system (CBRS) is appropriate for an experince-rich domain, while a rule-based system performs reasonably well in a knowledge-rich application environment. Performance of a CBRS suffers when past experience is not readily available. A generalized case-based reasoning system (GCBRS) is proposed to remedy this weakness by incorporating domain theories represented as generalization rules. With these rules, previous experience (stored as cases) can be generalized so that the possibility of solving a new case is higher than it would be when case-based reasoning is used alone. The architecture and the inference mechanism of a GCBRS are discussed in this article. A portfolio management support system based upon the proposed GCBRS architecture is presented to demonstrate the feasibility of using GCBRS for developing a decision support system in a knowledge-poor and experience-poor domain. This article concludes with a discussion of future research.