A Hybrid Knowledge and Model Approach for Reviewer Assignment

Authors:
Yong-Hong Sun;Jian Ma;Zhi-Ping Fan;Jun Wang
Affiliations:
City University of Hong Kong Kowloon, Hong Kong;City University of Hong Kong Kowloon, Hong Kong;Northeastern University, Shenyang, 110004, China;Northeastern University, Shenyang, 110004, China
Venue:
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Year:
2007

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Abstract

In R&D project selection, experts (or external reviewers) always play a very important role because their opinions will have great influence on the outcome of the project selection. It is also undoubted that experts with high expertise level will make useful and professional judgments on the projects to be selected. So, how to assign the most appropriate experts to the relevant proposals is a very significant issue. This paper presents a hybrid knowledge and model approach which integrates mathematical decision models with knowledge rules, for the assignment of experts to review of R&D project proposals. The approach can be applied to government funding agencies in China and other countries.