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, Department of Information Systems, 83 Tat Chee Ave., Kowloon Tong, Kowloon, Hong Kong;City University of Hong Kong, Department of Information Systems, 83 Tat Chee Ave., Kowloon Tong, Kowloon, Hong Kong;Northeastern University, School of Business Administration, Shenyang, 110004, China;Northeastern University, School of Business Administration, Shenyang, 110004, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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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 external reviewers to R&D project proposals. The approach can be applied to government funding agencies in China and other countries.