Title: Acquisition of compound skills and learning costs for expanding competence sets
Authors: Hu, YC
Chen, RS
Tzeng, GH
Chiu, YJ
科技管理研究所
資訊管理與財務金融系 註:原資管所+財金所
Institute of Management of Technology
Department of Information Management and Finance
Keywords: competence set;data mining;neural networks;fuzzy sets;integer programming.
Issue Date: 1-Sep-2003
Abstract: For each decision problem, there is a competence set consisting of ideas, knowledge, information, and skills for solving that problem. When decision makers have not acquired the competence set, it is more difficult for them to make decisions. In order to effectively acquire a needed competence set to cope with the problem they face, finding an appropriate learning sequence for acquiring needed single skills for decision makers, the so-called competence set expansion, is very necessary. A compound skill represents a collection of single skills that might be acquired, and some useful compound skills can be added to the needed competence set to help acquire some single skills. To effectively expand the competence set, effective acquisitions of compound skills and learning costs are both necessary. This paper thus proposes a data mining technique to extract potentially useful compound skills from single skills. Subsequently, an effective method is proposed to obtain the learning cost between any two skills. A computer simulation is employed to further show that it is feasible to use those potentially useful compound skills to facilitate the acquisition of single skills through a known integer programming method for expanding the competence set. (C) 2003 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/S0898-1221(03)90146-5
http://hdl.handle.net/11536/27546
ISSN: 0898-1221
DOI: 10.1016/S0898-1221(03)90146-5
Journal: COMPUTERS & MATHEMATICS WITH APPLICATIONS
Volume: 46
Issue: 5-6
Begin Page: 831
End Page: 848
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