Yong Jin Jeong , Kyoung Han Kim , Hyun Kyo Lim , Yong Hwan Kim , Youn Hee Han

KIPS Transactions on Software and Data Engineering, Vol. 4, No. 8, pp. 321-330, Aug. 2015
10.3745/KTSDE.2015.4.8.321,   PDF Download:

Abstract

In journal manuscript submission and review systems, authors can submit their manuscript at any time and editorial members are struggling to find proper reviewers for the submitted manuscripts and assign them to such reviewers. In order to solve this problem, we propose a greedy algorithm and a genetic algorithm to recommend proper reviewers for the submitted manuscripts. The proposed algorithms evaluate reviewers`` speciality for the submitted manuscripts by using the submitted manuscripts`` keywords and the reviewers expertises. In addition to that, they take the fairness among the reviewers`` speciality and the review frequency for consideration. To verify the proposed algorithms, we apply them to the JIPS manuscript submission and review system that the Korea Information Processing Society has operated, and present the results in this paper. By performing the performance evaluation of the proposed algorithms, we finally show that the genetic algorithm outperforms the greedy algorithm in terms of the recommended reviewers`` fitness.

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