A semantic fuzzy expert system for a fuzzy balanced scorecard

被引:41
作者
Bobillo, Fernando [1 ]
Delgado, Miguel [1 ]
Gomez-Romero, Juan [1 ]
Lopez, Enrique [2 ]
机构
[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, ETSI Informat, E-18071 Granada, Spain
[2] Univ Leon, Econ & Business Management Dept, E-24071 Leon, Spain
关键词
Knowledge-based systems; Expert systems; Ontologies semantic web; Applied economy; Balanced scorecard; Fuzzy logic; WEB; PROTEGE;
D O I
10.1016/j.eswa.2007.09.020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Balanced scorecard is a widely recognized tool to support decision making in business management. Unfortunately, current balanced scorecard-based systems present two drawbacks: they do not allow to de. ne explicitly the semantics of the underlying knowledge and they are not able to deal with imprecision and vagueness. To overcome these limitations, in this paper we propose a semantic fuzzy expert system which implements a generic framework for the balanced scorecard. In our approach, knowledge about balanced scorecard variables is represented using an OWL ontology, therefore allowing reuse and sharing of the model among different companies. The ontology acts as the basis for the fuzzy expert system, which uses highly interpretable fuzzy IF-THEN rules to infer new knowledge. Results are valuable pieces of information to help managers to improve the achievement of the strategic objectives of the company. A main contribution of this work it that the system is general and can be customized to adapt to different scenarios. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:423 / 433
页数:11
相关论文
共 34 条
[1]  
[Anonymous], 2003, Journal of the Eastern Asia Society for Transportation Studies
[2]  
[Anonymous], 2004, J. of Web Semantics
[3]   The Semantic Web - A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities [J].
Berners-Lee, T ;
Hendler, J ;
Lassila, O .
SCIENTIFIC AMERICAN, 2001, 284 (05) :34-+
[4]  
BLANCO I, 2005, P JOINT 4 EUSFLAT 11, P106
[5]  
Chou T.Y., 2001, MARIT POLICY MANAG, V28, P375, DOI DOI 10.1080/03088830110049951
[6]  
Damásio CV, 2006, RuleML 2006: Second International Conference on Rules and Rule Markup Languages for the Semantic Web, Proceedings, P97
[7]  
Dubois D, 2017, HANDBOOK OF CATEGORIZATION IN COGNITIVE SCIENCE, 2ND EDITION, P1029, DOI 10.1016/B978-0-08-101107-2.00041-5
[8]   Using JessTab to integrate Protege and Jess [J].
Eriksson, H .
IEEE INTELLIGENT SYSTEMS, 2003, 18 (02) :43-50
[10]  
Friedman-Hill E., 2003, Jess in Action: Java Rule-Based Systems