A Modular Diversity Based Reviewer Recommendation System
Abstract
A new approach for solving the problem of reviewer recommendation for conference or journal submissions is proposed. Instead of assigning one best reviewer and then looking for a second-best match, we want to start from a single reviewer and look for a diverse group of other possible candidates, that would complement the first one in order to cover multiple areas of the review. We present the idea of an overall modular system for determining a grouping of reviewers, as well as three modules for such a system: a keyword-based module, a social graph module, and a linguistic module. The added value of modular diversity is seen primarily for larger groups of reviewers. The paper also contains a proof of concept of the method.
Keywords
recommendation
Cite as
Maleszka, M., Maleszka, B., Krol, D., Hernes, M., Martins, D., Homann, L., & Vossen, G. (2020). A Modular Diversity Based Reviewer Recommendation System. In Paweł, S., Marcin, P., Marek, K., & Chutimet, S. (Eds.), Intelligent Information and Database Systems (pp. 550–561). Communications in Computer and Information Science (CCIS): Vol. 1178. Heidelberg: Springer.Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2020
Conference
12th Asian Conference on Intelligent Information and Database Systems (ACIIDS)
Venue
Phuket
Volume
1178
Book title
Intelligent Information and Database Systems
Editor
Paweł Sitek, Marcin Pietranik, Marek Krótkiewicz, Chutimet Srinilta
Start page
550
End page
561
Volume
1178
Title of series
Communications in Computer and Information Science (CCIS)
Publisher
Springer
Place
Heidelberg
Language
English
ISSN
1865-0929
ISBN
978-3-030-42057-4
DOI
Full text