A Modular Diversity Based Reviewer Recommendation System

Maleszka M., Maleszka B., Krol D., Hernes M., Martins D., Homann L., Vossen G.


Zusammenfassung

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.

Schlüsselwörter
recommendation



Publikationstyp
Forschungsartikel in Sammelband (Konferenz)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2020

Konferenz
12th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

Konferenzort
Phuket

Band
1178

Buchtitel
Intelligent Information and Database Systems

Herausgeber
Paweł Sitek, Marcin Pietranik, Marek Krótkiewicz, Chutimet Srinilta

Erste Seite
550

Letzte Seite
561

Band
1178

Reihe
Communications in Computer and Information Science (CCIS)

Verlag
Springer

Ort
Heidelberg

Sprache
Englisch

ISSN
1865-0929

ISBN
978-3-030-42057-4

DOI

Gesamter Text