A hybrid knowledge and model approach for reviewer assignment
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 817-824 |
| Journal / Publication | Expert Systems with Applications |
| Volume | 34 |
| Issue number | 2 |
| Publication status | Published - Feb 2008 |
Link(s)
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.
Research Area(s)
- Assignment problem, Decision support systems, Knowledge-based systems, R&D project selection
Citation Format(s)
A hybrid knowledge and model approach for reviewer assignment. / Sun, Yong-Hong; Ma, Jian; Fan, Zhi-Ping; Wang, Jun.
In: Expert Systems with Applications, Vol. 34, No. 2, 02.2008, p. 817-824.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
