Systematic mapping of automated reviewer recommendation solutions

dc.contributor.author Decoppet, Guillermo Omar
dc.contributor.author San Martín, Patricia Silvana
dc.date.accessioned 2026-03-12T22:50:33Z
dc.date.available 2026-03-12T22:50:33Z
dc.date.issued 2024-10-18
dc.description.abstract The increase in scientific production has generated a recurring problem on a global scale in the recommendation of reviewers for scientific journals and academic events, incentivizing the emergence of a significant diversity of automated solutions. This article presents a systematic review of these reviewer recommendation solutions published in scientific journals and academic events in the period 2018-2023. Methodologically, the final selection focused on the analysis of twenty-five articles. It covered the domain of reviewer recommendation solutions, their methods, factors and the data sets utilized. The results achieved systematize the diverse types of proposed solutions allowing to observe the similarities between the different methods. It is estimated that the present mapping provides an original survey on this problem that provides well-founded comparative information to support future research on reviewer recommendations.
dc.identifier.citation Decoppet, Guillermo O. & San Martin, Patricia S. (2024). Systematic mapping of automated reviewer recommendation solutions. In: Journal of Computer Science and Technology, 24(2), e16.
dc.identifier.other https://doi.org/10.24215/16666038.24.e16
dc.identifier.uri https://repositorio.uai.edu.ar/handle/123456789/4707
dc.language.iso en
dc.publisher Facultad de Informática, Universidad Nacional de La Plata
dc.subject natural language processing
dc.subject peer review
dc.subject recovery models
dc.subject selection process
dc.title Systematic mapping of automated reviewer recommendation solutions
dc.title.alternative Mapeo Sistemático de las Soluciones Automatizadas de Recomendación de Revisores
dc.type ARTICULO
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