How near-duplicate detection improves editors' and authors' publishing experience
Yury Kashnitsky, Vaishnavi Kandala, Egbert van Wezenbeek, IJsbrand Jan, Aalbersberg, Catriona Fennell, Georgios Tsatsaronis
TL;DR
This paper presents a near-duplicate detection system that enhances the publishing process by identifying simultaneous submissions, preventing duplicate publications, and improving article transfer, thereby streamlining editors' and authors' experiences.
Contribution
It introduces a novel near-duplicate detection system tailored for manuscript content to address multiple issues in academic publishing.
Findings
Effective identification of simultaneous submissions
Prevention of duplicate published articles
Enhanced article transfer process
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Web Data Mining and Analysis · Data Quality and Management