Abstract
Research into Reviewer Assignment Problem (RAP) is still in its early stage but there is great world-wide interest, as the foregoing process of peer-review which is the brickwork of science authentication. The RAP approach can be divided into three phases: identifying assignment procedure, computing the matching degree between manuscripts and reviewers, and optimizing the assignment so as to achieve the given objectives. Methodologies for addressing the above three phases have been developed from a variety of research disciplines, including information retrieval, artificial intelligent, operations research, etc. This survey is not only to cover variations of RAP that have appeared in the literature, but also to identify the practical challenge and current progress for developing intelligent RAP systems.
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References
Basu, C., Hirsh, H., Cohen, W.: Recommendation as Classification: Using Social and Content-based Information in Recommendation. In: 15th national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, pp. 714–720. AAAI, USA (1998)
Basu, C., Hirsh, H., Cohen, W., Nevill-Manning, C.: Technical paper recommendation: A study in combining multiple information sources. Journal of Artificial Intelligence Research 14, 231–252 (2001)
Bausch, D.O., Brown, G.G., Hundley, D.R., Rapp, S.H., Rosenthal, R.E.: Mobilizing Marine Corps Officers. Interfaces 21(4), 26–38 (1991)
Benferhat, S., Lang, J.: Conference Paper Assignment. International Journal of Intelligent Systems 16, 1183–1192 (2001)
Biswas, H.K., Hasan, M.M.: Using Publications and Domain Knowledge to Build Research Profiles: an Application in Automatic Reviewer Assignment. In: 2007 International Conference on Information and Communication Technology, pp. 82–86 (2007)
Cameron, D., Aleman-Meza, B., Arpinar, B.: Collecting Expertise of Researchers for Finding Relevant Experts in a Peer-Review Setting. In: First International ExpertFinder Workshop (2007)
Caron, G., Hansen, P., Jaumard, B.: The assignment problem with seniority and job priority constraints. Operations Research 47(3), 449–454 (1999)
Carter, M.W., Tovey, C.A.: When is the classroom assignment problem hard? Operations Research 40(1), S28–S39 (1992)
Casati, F., Giunchiglia, F., Marchese, M.: Publish and perish: Why the Current Publication and Review Model is Killing Research and Wasting Your Money, http://www.acm.org/ubiquity/views/v8i03_fabio.html
Cohen, P.R., Kjeldsen, R.: Information retrieval by constrained spreading activation in semantic network. Information Processing & Management 23(4), 255–268 (1987)
Cohen, W., Fan, W.: Web-collaborative Filtering: Recommending Music by Crawling the Web. Computer Networks 33(1-6), 685–698 (2000)
Cook, W.D., Golany, B., Kress, M., Penn, M., Raviv, T.: Optimal Allocation of Proposals to Reviewers to Facilitate Effective Ranking. Management Science 51(4), 655–661 (2005)
Dell’Amico, M., Martello, S.: The k-cardinality assignment problem. Discrete Applied Mathematics 76(1-3), 103–121 (1997)
Dumais, S., Nielsen, J.: Automating the assignment of submitted manuscripts to reviewers. Research and Development in information Retrieval, 233–244 (1992)
Geller, J.: How IJCAI 1999 can prove the value of AI by using AI. In: 15th International Joint Conference on Artificial Intelligence, pp. 55–58 (1997)
Geller, J., Scherl, R.: Challenge: Technology for Automated Reviewer Selection (1997), http://njit.edu/~geller/finalchall.ps1997
Goldsmith, J., Solan, R.H.: The AI Conference Paper Assignment Problem, http://www.cs.uic.edu/~sloan/my-papers/GodlsmithSloanPaperAssignment.pdf
Gupta, D., Digiovanni, M., Narita, H., Goldberg, K.: Jester 2.0: A new Lineartime Collaborative Filtering Algorithm Applied to Jokes. In: Workshop on Recommender Systems at ACM SIGIR 1999 (1999)
Hansen, P., Wendell, R.E.: A note on airline commuting. Interfaces 11(12), 85–87 (1982)
Hartvigsen, D., Wei, J.C., Czuchlewski, R.: The Conference Paper-Reviewer Assignment Problem. Decision Sciences 30(3), 865–876 (1999)
Hettich, S., Pazzani, M.J.: Mining for Proposal Reviewers: Lessons Learned at the National Science Foundation. In: 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 862–871. ACM Press, New York (2006)
Hill, W., Stead, L., Rosenstein, M., Furnas, G.: Recommending and Evaluating Choices in a Virtual Community of Use. In: SIGCHI conference on Human factors in computing systems, pp. 195–201. ACM Press/Addison-Wesley Publishing Co., New York (1995)
Hofmann, T.: Probabilistic Latent Semantic Analysis. In: 15th Conference on Uncertainty in Artificial Intelligence, pp. 289–296 (1999)
Janak, S.L., Taylor, M.S., Floudas, C.A., Burka, M., Mountzizris, T.J.: Novel and Effective Integer Optimization Approach for the NSF Panel-Assignment Problem: A Multiresource and Preference-Constrained Generalized Assignment Problem. Ind. Eng. Chem. Res. 45(1), 258–265 (2006)
Klingman, D., Phillips, N.: Topological and computational aspects of preemptive multicriteria military personnel assignment problems. Manage. Sci. 30(1), 1362–1375 (1984)
Konstan, J., Miller, B., Maltz, D., Herlocker, L., Gordon, L., Riedl, J.: Grouplens: Applying Collaborative Filtering to Usenet News. Communications of the ACM 40(3), 77–87 (1997)
LeBlanc, L.J., Randels, D., Swann, T.K.: Heery International’s Spreadsheet Optimization Model for Assigning Managers to Construction Projects. INTERFACE 30(6), 95–106 (2000)
Merelo-Guervós, J.J., Castillo-Valdivieso, P.: Conference Paper Assignment Using a Combined Greedy/ Evolutionary Algorithm. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 602–611. Springer, Heidelberg (2004)
Merelo-Guervós, J.J., García-Castellano, F.J., Castillo, P.A., Arenas, M.G.: How Evolutionary Computation and Perl saved my conference. In: Sánchez, L. (ed.) Segundo Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados, pp. 93–99 (2003)
Popescul, A., Ungar, L.H., Pennock, D.M., Lawrence, S.: Probabilistic Models for Unified Collaborative and Content-base Recommendation in Sparse-Data Environments. In: 17th Conference on Uncertainty in Artificial Intelligence, pp. 437–444. Morgan Kaufmann Publishers Inc., San Francisco (2001)
Rodriguez, M.A., Bollen, J., Van de Sompel, H.: Mapping the Bid Behavior of Conference Referees. Journal of Informetrics 1(1), 62–82 (2007)
Rodriguez, M.A., Bollen, J.: An Algorithm to Determine Peer-Reviewers. Arxiv preprint cs.DL/0605112 (2006)
Schirrer, A., Doerner, K.F., Hartl, R.F.: Reviewer Assignment for Scientific Articles using Memetic Algorithms. OR/CS Interfaces Series 39, 113–134 (2007)
Scott, A.: Peer review and the relevance of science. Futures 39, 827–845 (2007)
Shardanand, U., Maes, P.: Social Information Filtering: Algorithms for Automating “Word of Mouth”. In: SIGCHI conference on Human factors in computing systems, pp. 210–217. ACM Press/Addison-Wesley Publishing Co., New York (1995)
Sun, Y.H., Ma, J., Fan, Z.P., Wang, J.: A Hybrid Knowledge and Model Approach for Reviewer Assignment. In: 40th Annual Hawaii International Conference on System Sciences, p. 47. IEEE Computer Society, Washington (2007)
Tian, Q., Ma, J., Liu, O.: A Hybrid Knowledge and Model System for R&D Project Selection. Expert Systems with Applications 23(3), 265–271 (2002)
Veronika, A., Riantini, L.S., Trigunarsyah, B.: Corrective Action Recommendation For Project Cost Variance in Construction Material Management. In: Kanok-Nukulchai, W., Munasinghe, S., Anwar, N. (eds.) 10th East Asia-Pacific Conference on Structural Engineering and Construction 2005, pp. 23–28 (2006)
Watanabe, S., Ito, T., Ozono, T., Shintani, T.: A Paper Recommendation Mechanism for the Research Support System Papits. In: International Workshop on Data Engineering Issues in E-Commerce, pp. 71–80 (2005)
Weber, R.: The Journal Review Process: a Manifesto for Change. Communications of the Association for Information Systems 2(2-3) (1999)
Yarowsky, D., Florian, R.: Taking the load off the conference chairs: towards a digital paper-routing assistant. In: 1999 Joint SIGDAT Conference on Empirical Methods in NLP and Very-Large Corpora (1999)
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Wang, F., Chen, B., Miao, Z. (2008). A Survey on Reviewer Assignment Problem. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds) New Frontiers in Applied Artificial Intelligence. IEA/AIE 2008. Lecture Notes in Computer Science(), vol 5027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69052-8_75
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DOI: https://doi.org/10.1007/978-3-540-69052-8_75
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