How near-duplicate detection improves editors' and authors' publishing experience

Autor: Kashnitsky, Yury, Kandala, Vaishnavi, van Wezenbeek, Egbert, Aalbersberg, IJsbrand Jan, Fennell, Catriona, Tsatsaronis, Georgios
Rok vydání: 2021
Předmět:
Druh dokumentu: Working Paper
Popis: We describe a system that helps identify manuscripts submitted to multiple journals at the same time. Also, we discuss potential applications of the near-duplicate detection technology when run with manuscript text content, including identification of simultaneous submissions, prevention of duplicate published articles, and improving article transfer service.
Comment: short paper, 2 pages, 1 figure, presented at Computational Research Integrity 2021 conference
Databáze: arXiv