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doi:10.1016/S0957-4174(02)00046-5    
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Copyright © 2002 Elsevier Science Ltd. All rights reserved.

A hybrid knowledge and model system for R&D project selection

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Qijia Tiana, b, Jian MaCorresponding Author Contact Information, E-mail The Corresponding Author, a and Ou Liua

a Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, People's Republic of China

b Department of Computer Science, Shandong University of Science and Technology, People's Republic of China


Available online 8 August 2002.

Abstract

Decision models and knowledge rules are widely used to assist in decision-making. They are common decision support devices that should be effectively managed in decision support systems. Research and development (R&D) project selection is a complicated and knowledge intensive decision-making process where decision models and knowledge rules play an important role. This paper presents a hybrid knowledge and model system, which integrates mathematical models with knowledge rules, for R&D project selection. The system is designed to support the whole decision process of R&D project selection and has been used in the selection of R&D projects in the National Natural Science Foundation of China (NSFC).

Author Keywords: Decision support systems; Knowledge-based systems; Model management; R&D project selection

Article Outline

1. Introduction
2. Background
3. The hybrid knowledge and model system
3.1. Architecture overview
3.2. Data base
3.3. Decision models
3.4. Knowledge rules
4. Implementation and application
5. Conclusions
References

Corresponding Author Contact Information Corresponding author. Tel.: +852-2788-8514; fax: +852-2784-4198; email: isjian@is.cityu.edu.hk


 
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