Accession number:20094712485268
Title: A rule-based CBR approach for expert finding and problem diagnosis
Authors:Tung, Yuan-Hsin (1); Tseng, Shian-Shyong (1); Weng, Jui- Feng (1); Lee, Tsung-Ping (1); Liao, Anthony Y.H. (2); Tsai, Wen-Nung (1)
Author affiliation:(1) Department of Computer Science and
Information Engineering, National Chiao Tung University, Taiwan; (2) Department of Information Science and Applications, Asia
University, Taiwan; (3) R and D Supporting Department, Telecommunication Lab., Chunghwa Telecom Co., Ltd., Taiwan Corresponding author:Tseng, S.-S.
(sstseng@asia.edu.tw)
Source title:Expert Systems with Applications Abbreviated source title:Expert Sys Appl Volume:37
Issue:3
Issue date:March 15, 2010 Publication year:2010 Pages:2427-2438 Language:English ISSN:09574174 CODEN:ESAPEH
Document type:Journal article (JA)
Publisher:Elsevier Ltd, Langford Lane, Kidlington, Oxford, OX5 1GB, United Kingdom
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.
Number of references:31 Main heading:Access control
Controlled terms:Bits - Block codes - Case based reasoning - Information retrieval - Knowledge based systems - Large scale systems - Security systems
Uncontrolled terms:CBR - Expert finding - Problem diagnosis - RBR - Role-based access control - Rule-based CBR
Classification code:961 Systems Science - 914.1 Accidents and Accident Prevention - 912.3 Operations Research - 903.3 Information Retrieval and Use - 903.1 Information Sources and Analysis - 731.1 Control Systems - 723.5 Computer Applications - 723.4.1 Expert Systems - 723.4 Artificial Intelligence - 723.1 Computer
Programming - 723 Computer Software, Data Handling and
Applications - 603.2 Machine Tool Accessories - 461.1 Biomedical Engineering
DOI:10.1016/j.eswa.2009.07.037 Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
