Paper Info
Title
A Study on the Reliability of Case-Based Reasoning Systems
Abstract
Case-based reasoning (CBR) is a methodology for problem solving, which suggests a solution to a new problem based on the previously-solved problems and their associated solutions. A key issue in this methodology is that can we always trust the solutions suggested by a case-based reasoning system? This paper studies the reliability of CBR systems at an overall level first. Factors affecting the reliability of a CBR system are discussed in this section, especially the property that whether its case library is compatible with the foundational assumption that "similar problems have similar solutions." After that, the reliability of an individual suggested solution is studied. Some existing approaches which can be employed to estimate the reliability of a single solution are compared in this section. To illustrate these ideas, some experiments and their results are also discussed in this paper. It is shown that if a case library attains a high compatibility, then a satisfactory result can be expected, and the reliability of a CBR system at an overall level can be improved by identifying the reliable solutions.
Year
DOI
Venue
2008
10.1109/ICDMW.2008.33
ICDM Workshops
Keywords
Field
DocType
associated solution,overall level,similar solution,cbr system,individual suggested solution,reliable solution,single solution,case-based reasoning,case-based reasoning system,case library,compatibility,iris,cognition,tropical cyclones,reliability,case based reasoning,classification,case base reasoning,noise measurement
Data mining,Distance measurement,Noise measurement,Compatibility (mechanics),Computer science,Artificial intelligence,Reasoning system,Case-based reasoning,Cognition,Machine learning
Conference
Citations 
PageRank 
References 
1
0.36
10
Authors
3
Name
Order
Citations
PageRank
Ke Wang1619.24
James N. K. Liu252944.35
Weimin Ma342726.76