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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8711


    Title: A rule-based CBR approach for expert finding and problem diagnosis
    Authors: Tung, Yuan-Hsin;Tseng, Shian-Shyong;Weng, Jui-Feng;Lee, Tsung-Ping1;Liao, Anthony Y.H.;Tsai, Wen-Nung
    Contributors: Department of Information Science and Applications
    Keywords: Bits;Block codes;Case based reasoning;Information retrieval;Knowledge based systems;Large scale systems;Security systems;CBR;Expert finding;Problem diagnosis;RBR;Role-based access control;Rule-based CBR
    Date: 2010-03
    Issue Date: 2010-04-07 21:34:03 (UTC+8)
    Publisher: Asia University
    Abstract: It is important to find the person with right expertise and the appropriate solutions in the specific field to solve a critical situation in a large complex system such as an enterprise level application. In this paper, we apply the experts' knowledge to construct a solution retrieval system for expert finding and problem diagnosis. Firstly, we aim to utilize the experts' problem diagnosis knowledge which can identify the error type of problem to suggest the corresponding expert and retrieve the solution for specific error type. Therefore, how to find an efficient way to use domain knowledge and the corresponding experts has become an important issue. To transform experts' knowledge into the knowledge base of a solution retrieval system, the idea of developing a solution retrieval system based on hybrid approach using RBR (rule-based reasoning) and CBR (case-based reasoning), RCBR (rule-based CBR), is proposed in this research. Furthermore, we incorporate domain expertise into our methodology with role-based access control model to suggest appropriate expert for problem solving, and build a prototype system with expert finding and problem diagnosis for the complex system. The experimental results show that RCBR (rule-based CBR) can improve accuracy of retrieval cases and reduce retrieval time prominently. © 2009 Elsevier Ltd. All rights reserved.
    Relation: Expert Systems with Applications 37(3):2427-2438
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

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