A case-based approach using inductive indexing for corporate bond rating

TitleA case-based approach using inductive indexing for corporate bond rating
Publication TypeJournal Article
Year of Publication2001
AuthorsShin K-shik, Han I
JournalDecision Support Systems
Volume32
Issue1
Start Page41
Date Published11/2001
ISSN0167-9236
KeywordsCase-based Reasoning, Corporate bond rating, Inductive learning
Abstract

Case-based reasoning CBR is a problem solving technique by re-using past cases and experiences to find a solution to Ž .
problems. The central tasks involved in CBR methods are to identify the current problem situation, find a past case similar to
the new one, use that case to suggest a solution to the current problem, evaluate the proposed solution, and update the
system by learning from this experience. In doing tasks, one of the critical issues in building a useful CBR system lies in the
application of general domain knowledge to the indexing of cases, which may support the retrieval of relevant cases to the
problem.
This paper investigates the effectiveness of inductive learning approach to case indexing process for business
classification tasks. We suggest this approach as a unifying framework to combine general domain knowledge and
case-specific knowledge. Our particular interest involves optimal or near optimal decision trees that represent an optimal
combination level between the two knowledge types. The proposed approach is demonstrated by applications to corporate
bond rating. q 2001 Elsevier Science B.V. All rights reserved.

URLhttp://www.sciencedirect.com/science/article/pii/S0167923601000999