Peerus Review: a tool for scientific experts finding
This addresses the need for efficient expert matching in academic peer review, but it appears incremental as it applies existing language modeling methods to a specific domain.
The authors tackled the problem of finding scientific experts for peer review by developing a tool that uses a language modeling technique trained on millions of papers to return a list of potential reviewers based on article details. The result is a retrieval algorithm implemented in the Peerus application, though no concrete performance numbers are provided.
We propose a tool for experts finding applied to academic data generated by the start-up DSRT in the context of its application Peerus. A user may submit the title, the abstract and optionnally the authors and the journal of publication of a scientific article and the application then returns a list of experts, potential reviewers of the submitted article. The retrieval algorithm is a voting system based on a language modeling technique trained on several millions of scientific papers.