A Hybrid Knowledge and Model Approach for Reviewer Assignment

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

9 Scopus Citations
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Author(s)

  • Yong-Hong Sun
  • Jian Ma
  • Zhi-Ping Fan
  • Jun Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the 40th Annual Hawaii International Conference on System Sciences
EditorsRalph H. Sprague, Jr.
Publication statusPublished - Jan 2007

Publication series

Name
ISSN (Print)1530-1605

Conference

Title40th Annual Hawaii International Conference on System Sciences 2007 (HICSS'07)
LocationHilton Waikoloa Village
PlaceUnited States
CityBig Island
Period3 - 6 January 2007

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.

Citation Format(s)

A Hybrid Knowledge and Model Approach for Reviewer Assignment. / Sun, Yong-Hong; Ma, Jian; Fan, Zhi-Ping; Wang, Jun.

Proceedings of the 40th Annual Hawaii International Conference on System Sciences. ed. / Ralph H. Sprague, Jr. 2007. 4076467.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review