MINARET: A Recommendation Framework for Scientific Reviewers
Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Open proceedings org
Abstract
We are witnessing a continuous growth in the size of scien tific communities and the number of scientific publications.
This phenomenon requires a continuous effort for ensuring
the quality of publications and a healthy scientific evalu ation process. Peer reviewing is the de facto mechanism
to assess the quality of scientific work. For journal editors,
managing an efficient and effective manuscript peer review
process is not a straightforward task. In particular, a main
component in the journal editors’ role is, for each submit ted manuscript, to ensure selecting adequate reviewers who
need to be: 1) Matching on their research interests with
the topic of the submission, 2) Fair in their evaluation of
the submission, i.e., no conflict of interest with the authors,
3) Qualified in terms of various aspects including scientific
impact, previous review/authorship experience for the jour nal, quality of the reviews, etc. Thus, manually selecting
and assessing the adequate reviewers is becoming tedious
and time consuming task.
We demonstrate MINARET, a recommendation framework
for selecting scientific reviewers. The framework facilitates
the job of journal editors for conducting an efficient and
effective scientific review process. The framework exploits
the valuable information available on the modern scholarly
Websites (e.g., Google Scholar, ACM DL, DBLP, Publons)
for identifying candidate reviewers relevant to the topic of
the manuscript, filtering them (e.g. excluding those with
potential conflict of interest), and ranking them based
on several metrics configured by the editor (user). The
framework extracts the required information for the rec ommendation process from the online resources on-the-fly
which ensures the output recommendations to be dynamic
and based on up-to-date information.
Description
Keywords
Citation
Moawad M.R. et al. (2019) “Minaret: A recommendation framework for scientific reviewers,” Advances in Database Technology - EDBT, 2019-March, pp. 538–541.