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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/18863

    Title: A Rule-based CBR Approach for Expert Finding and Problem Diagnosis,
    Authors: 曾憲雄;Tseng, Shian-Shyong
    Contributors: 資訊多媒體應用學系
    Keywords: Rule-based CBR;RBR;CBR;Expert finding;Role-based access control;Problem diagnosis
    Date: 2009
    Issue Date: 2012-11-26 15:09:50 (UTC+8)
    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.
    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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