Elicitation of knowledge from multiple experts using network inference

被引:16
|
作者
Rush, R
Wallace, WA
机构
[1] Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, Troy
关键词
knowledge acquisition; multiple experts; network inference; quality of rules; influence diagram;
D O I
10.1109/69.634748
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Eliciting knowledge from multiple experts usually entails the use of groups, and thus is subject to the problems inherent in group dynamics. We present a technique for multiple expert knowledge acquisition that does not rely upon the use of groups and can take advantage of technological advances in communications and computing, i.e., the Internet. The approach uses influence diagrams to represent the individual expert's understanding of the problem situation and develops a Multiple Expert Influence Diagram (MEID), a composite representation of the experts' knowledge. Following a review of present methods for multiple expert knowledge elicitation, we formally define the MEID, describe its manner of construction, and discuss its interpretation. We continue with a review of the issues to be faced in implementation of the technique, and give an illustrative example. Finally, we emphasize the need to provide users of decision aids with defensible measures of the quality of the rules produced by these aids. The MEID- approach is intended to serve as a first step in this direction.
引用
收藏
页码:688 / 696
页数:9
相关论文
共 50 条
  • [41] Predictive analysis network tool for human knowledge elicitation and reasoning
    Thompson, Jennifer
    Bradley, Jessica
    [J]. 2007 PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2007, : 1219 - 1224
  • [42] MODELING FOR CONTROL KNOWLEDGE IN SINTERING PROCESS USING NEURAL NETWORK AND FUZZY INFERENCE
    MATSUDA, K
    TAMURA, N
    NOSE, K
    NODA, T
    OKATA, T
    OSUZU, K
    [J]. TETSU TO HAGANE-JOURNAL OF THE IRON AND STEEL INSTITUTE OF JAPAN, 1992, 78 (07): : 1045 - 1052
  • [43] FROM ELICITATION TO STRUCTURING OF ADDITIVE MANUFACTURING KNOWLEDGE
    Grandvallet, Christelle
    Pourroy, Franck
    Prudhomme, Guy
    Vignat, Frederic
    [J]. DS87-6: PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN (ICED 17) VOL 6: DESIGN INFORMATION AND KNOWLEDGE, 2017, : 141 - 150
  • [44] Protein network inference from multiple genomic data: a supervised approach
    Yamanishi, Y.
    Vert, J. -P.
    Kanehisa, M.
    [J]. BIOINFORMATICS, 2004, 20 : 363 - 370
  • [45] ACQUIRING STRATEGIC KNOWLEDGE FROM EXPERTS
    GRUBER, TR
    [J]. INTERNATIONAL JOURNAL OF MAN-MACHINE STUDIES, 1988, 29 (05): : 579 - 597
  • [46] Extraction of Belief Knowledge from a Relational Database for Quantitative Bayesian Network Inference
    Wang, LiMin
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
  • [47] Elicitation using multiple price list formats
    Andersen, Steffen
    Harrison, Glenn W.
    Lau, Morten Igel
    Rutstrom, E. Elisabet
    [J]. EXPERIMENTAL ECONOMICS, 2006, 9 (04) : 383 - 405
  • [48] Elicitation using multiple price list formats
    Steffen Andersen
    Glenn W. Harrison
    Morten Igel Lau
    E. Elisabet Rutström
    [J]. Experimental Economics, 2009, 12 : 365 - 366
  • [49] Elicitation using multiple price list formats
    Steffen Andersen
    Glenn W. Harrison
    Morten Igel Lau
    E. Elisabet Rutström
    [J]. Experimental Economics, 2006, 9 (4) : 383 - 405
  • [50] Developing Knowledge Asset Valuation Model using Knowledge Experts
    Wai, Wong Man
    Ramasamy, Ammuthavali
    Othman, Marini bt
    [J]. PROCEEDINGS OF KNOWLEDGE MANAGEMENT INTERNATIONAL CONFERENCE (KMICE) 2016, 2016, : 87 - 92