Aksoy, M., Yanik, S., & Amasyali, M. F. (2023). Reviewer Assignment Problem: A Systematic Review of the Literature. Journal of Artificial Intelligence Research, 76, 761-827. https://doi.org/10.1613/jair.1.14318
Bouanane, K., Medakene, A. N., Benbelghit, A., & Belhaouari, S. B. (2024). FairColor: An efficient algorithm for the balanced and fair reviewer assignment problem.
Information Processing & Management,
61(6), 103865.
https://doi.org/10.1016/j.ipm.2024.103865
Carpenter, J. M., Corvillón, A., & Shah, N. B. (2025). Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMA. Publications of the Astronomical Society of the Pacific, 137(3), 034501. https://doi.org/10.1088/1538-3873/adb5c1
Charlin, L., Zemel, R. S., & Boutilier, C. (2011). A Framework for Optimizing Paper Matching. In UAI (Vol. 11, pp. 86-95). https://doi.org/10.48550/arXiv.1202.3706
Cook, W. D., Golany, B., Kress, M., Penn, M., & Raviv, T. (2005). Optimal allocation of proposals to reviewer’sto facilitate effective ranking. Management Science, 51(4), 655-661. https://doi.org/10.1287/mnsc.1040.0290
Daraei, F. (2022). Combining Genetic Algorithms And Motor Nest Optimization To Solve The Supplier's Selection Problem, Journal of Intelligent Marketing Management, 3(3), 41-81.
Daş, G. S., & Göçken, T. (2014). A fuzzy approach for the reviewer assignment problem. Computers & industrial engineering, 72, 50-57. https://doi.org/10.1016/j.cie.2014.02.014
Delavar, A. (2008). Research method in psychology and educational sciences. Tehran.
Fan, Z. P., Chen, Y., Ma, J., & Zhu, Y. (2009). Decision support for proposal grouping: A hybrid approach using knowledge rule and genetic algorithm. Expert systems with applications, 36(2), 1004-1013. https://doi.org/10.1016/j.eswa.2007.11.011
Hettich, S., & Pazzani, M. J. (2006). Mining for proposal reviewer’s: lessons learned at the national science foundation. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 862-871). https://doi.org/10.1145/1150402.1150521
Hoang, D. T., Nguyen, N. T., Collins, B., & Hwang, D. (2021). Decision support system for solving reviewer assignment problem. Cybernetics and Systems, 52(5), 379-397. https://doi.org/10.1080/01969722.2020.1871227
Immanuel, S. D., & Chakraborty, U. K. (2019). Genetic algorithm: An approach on optimization. In 2019 international conference on communication and electronics systems (ICCES) (pp. 701-708). https://doi: 10.1109/ICCES45898.2019.9002372.
Kamps, J., Marx, M., Mokken, R. J., & De Rijke, M. (2004). Using WordNet to measure semantic orientations of adjectives. In Lrec (Vol. 4, pp. 1115-1118).
Kolasa, T., & Krol, D. (2011). A survey of algorithms for paper-reviewer assignment problem. IETE Technical Review, 28(2), 123-134. https://doi.org/10.4103/0256-4602.78092
Kalmukov, Y. (2013). Describing papers and reviewer’s' competences by taxonomy of keywords. arXiv preprint arXiv:1309.6527. https://doi.org/10.48550/arXiv.1309.6527
Karimzadehgan, M., Zhai, C., & Belford, G. (2008). Multi-aspect expertise matching for review assignment.
In Proceedings of the 17th ACM conference on Information and knowledge management (pp. 1113-1122).
https://doi.org/10.1145/1458082.1458230
Karimzadehgan, M., & Zhai, C. (2012). Integer linear programming for constrained multi-aspect committee review assignment. Information processing & management, 48(4), 725-740. https://doi.org/10.1016/j.ipm.2011.09.004
Land, A. H., & Doig, A. G. (2009). An automatic method for solving discrete programming problems. In 50 Years of Integer Programming 1958-2008: (pp. 105-132). https://doi.org/10.1007/978-3-540-68279-0_5
Leyton-Brown, K., Nandwani, Y., Zarkoob, H., Cameron, C., Newman, N., & Raghu, D. (2024). Matching papers and reviewer’sat large conferences. Artificial Intelligence, 331, 104119. https://doi.org/10.1016/j.artint.2024.104119
Li, K., Cao, Z., & Qu, D. (2017). Fair reviewer assignment considering academic social network. In Web and Big Data: First International Joint Conference, APWeb-WAIM 2017, Beijing, China, July 7–9, 2017, Proceedings, Part I 1 (pp. 362-376). https://doi.org/10.1007/978-3-319-63579-8_28
Li, X., & Watanabe, T. (2013). Automatic Paper-to-reviewer Assignment, Based on the Matching Degree of the Reviewers. Procedia Computer Science, 22, 633-642. https://doi.org/10.1016/j.procs.2013.09.144
Long, C., Wong, R. C. W., Peng, Y., & Ye, L. (2013). On good and fair paper-reviewer assignment. In 2013 IEEE 13th international conference on data mining (pp. 1145-1150).
Luo, X. G., Li, H. J., Zhang, Z. L., & Jiang, W. (2024). Multi-objective optimization for assigning reviewer’sto proposals based on social networks. Journal of Management Science and Engineering. 9(3), 419-439. https://doi.org/10.1016/j.jmse.2024.05.001
Mimno, D., & McCallum, A. (2007). Expertise modeling for matching papers with reviewer’s. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 500-509). https://doi.org/10.1145/1281192.1281247
Monteiro, R. D. (1997). School of Industrial and Systems Engineering Georgia Institute of Technology, Atlanta, GA 30332.
Neshati, M., Beigy, H., & Hiemstra, D. (2014). Expert group formation using facility location analysis. Information processing & management, 50(2), 361-383. https://doi.org/10.1016/j.ipm.2013.10.001
Ribeiro, A. C., Sizo, A., & Reis, L. P. (2023). Investigating the reviewer assignment problem: A systematic literature review.
Journal of Information Science,
0(0).
https://doi.org/10.1177/01655515231176668
Rordorf, D., Käser, J., Crego, A., & Laurenzi, E. (2023). A Hybrid Intelligent Approach Combining Machine Learning and a Knowledge Graph to Support Academic Journal Publishers Addressing the Reviewer Assignment Problem (RAP). In AAAI Spring Symposium: MAKE. https://doi.org/10.26041/fhnw-11149
Schirrer, A., Doerner, K. F., & Hartl, R. F. (2007). Reviewer assignment for scientific articles using memetic algorithms. Metaheuristics: Progress in Complex Systems Optimization, 113-134. https://doi.org/10.1007/978-0-387-71921-4_6
Simon, H. A., & Newell, A. (1958). Heuristic problem solving: The next advance in operations research. Operations research, 6(1), 1-10. https://doi.org/10.1287/opre.6.1.1
Stelmakh, I., Wieting, J., Neubig, G., & Shah, N. B. (2023). A gold standard dataset for the reviewer assignment problem. arXiv preprint arXiv:2303.16750. https://doi.org/10.48550/arXiv.2303.16750
Xu, Y., Ma, J., Sun, Y., Hao, G., Xu, W., & Zhao, D. (2010). A decision support approach for assigning reviewer’sto proposals. Expert Systems with Applications, 37(10), 6948-6956. https://doi.org/10.1016/j.eswa.2010.03.027
Wang, F., Zhou, S., & Shi, N. (2013). Group-to-group reviewer assignment problem. Computers & operations research, 40(5), 1351-1362. https://doi.org/10.1016/j.cor.2012.08.005
Wi, H., Oh, S., Mun, J., & Jung, M. (2012). A team formation model based on knowledge and collaboration. IEEE Engineering Management Review, 40(1), 44-57. https://doi.org/10.1016/j.eswa.2008.12.031
Zhao, X., & Zhang, Y. (2022). Reviewer assignment algorithms for peer review automation: A survey. Information Processing & Management, 59(5), 103028. https://doi.org/10.1016/j.ipm.2022.103028