EVALUATING THE EFFECTIVENESS OF KNOWLEDGE-RETRIEVAL AIDS FOR FAULT-DIAGNOSIS TASKS

Abstract

ABSTRACT The mechanism of knowledge retrieval is the key factor regarding whether users can efficiently apply a knowledge-based system. The effects case-based reasoning (CBR) retrieval and traditional key-term knowledge retrieval have on the performance of fault-diagnosis tasks were compared. The study was conducted using a split-plot factorial design: Two knowledge-retrieval aids by two problem complexities. Twenty subjects participated in the experiment and were randomly assigned to one of two groups. ANOVA results show that the fault-diagnosis times of the subjects in the CBR knowledge-retrieval group were significantly shorter than those of the key-term knowledge-retrieval group. In addition, the correct fault-diagnosis rates of the CBR knowledge-retrieval group were significantly higher than those of the key-term knowledge-retrieval group. The differences were more significant when the diagnosis tasks were of higher degrees of complexity. The results demonstrate that the CBR retrieval aid can improve the performance of fault-diagnosis tasks. It is therefore suggested that algorithm-based knowledge browsing and retrieval aids should be included in the development of knowledge-based systems to support users in interacting with these systems.