Automatic Reviewers Assignment to a Research Paper Based on Allied References and Publications Weight
Tamim Al Mahmud, B M Mainul Hossain, Dilshad Ara

TL;DR
This paper presents an automated method for assigning the most suitable reviewers to research papers by analyzing references, extracting keywords, and ranking researchers based on bibliometric indicators and web data.
Contribution
It introduces a novel automated approach combining reference analysis, web keyword extraction, and researcher ranking to improve reviewer selection accuracy.
Findings
Successfully identifies suitable reviewers using bibliometric and web data.
Reduces manual effort in reviewer assignment process.
Enhances review quality by selecting expert reviewers.
Abstract
Everyday, a vast stream of research documents is submitted to conferences, anthologies, journals, newsletters, annual reports, daily papers, and various periodicals. Many such publications use independent external specialists to review submissions. This process is called peer review, and the reviewers are called referees. However, it is not always possible to pick the best referee for reviewing. Moreover, new research fields are emerging in every sector, and the number of research papers is increasing dramatically. To review all these papers, every journal assigns a small team of referees who may not be experts in all areas. For example, a research paper in communication technology should be reviewed by an expert from the same field. Thus, efficiently selecting the best reviewer or referee for a research paper is a big challenge. In this research, we propose and implement program that…
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