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Evaluating the Effectiveness of Knowledge-Retrieval AIDS for Fault-Diagnosis Tasks

知識檢索輔助系統對於故障診斷作業績效之影響

摘要


知識檢索之輔助機制是決定人員能否有效地使用知識基系統之關鍵因素。本研究評估與比較案例式推理法(CBR)知識檢索輔助傳統之關鍵字知識檢索輔助系統在故障診斷作業之輔助績效。本研究之實驗情境有2(知識檢索輔助方式)X2(問題複雜度)等4種,其中知識檢索輔助式為受試者間變項,作業複雜度則為受試者內變項。由ANOVA分析結果顯示,CBR知識檢索輔助組之受試者所花的故障診斷時間顯著地低於關鍵字檢索輔助組。尤其,當問題複雜度提高時,CBR知識檢索輔助組之受試者之故障診斷績效更顯著地高於關鍵字檢索輔助組。由研究結果顯示,CBR知識檢索輔助能有效地增進故障診斷績效。因此,建議有關知識基系統之發展有必要將以演算推理為基礎之知識瀏覽與檢索機制列入考慮,以增進人員與系統間之互動效益。

並列摘要


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. 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.

參考文獻


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