A multiview clustering approach to identify out-of-scope submissions in peer review

Tirthankar Ghosal, Debomit Dey, Avik Dutta, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Despite criticisms, peer review is still the only widely accepted method for research validation. The first stage in academic peer review begins at the editor's desk where one essential job of the editor is to identify and reject inappropriate out-of-scope submissions. Here in this work, we investigate if we could assist the editor in identifying potential out-of-scope submissions. We view a paper from multiple perspectives and devise a multiview clustering approach to group in-scope and out-of-scope articles. Our semi-supervised approach requires less training data yet achieves high performance. Our initial investigation yields promising results and has the potential to reduce the first turn-around time for journal submissions.

Original languageEnglish
Title of host publicationProceedings - 2019 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019
EditorsMaria Bonn, Dan Wu, Stephen J. Downie, Alain Martaus
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages392-393
Number of pages2
ISBN (Electronic)9781728115474
DOIs
StatePublished - Jun 2019
Externally publishedYes
Event19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019 - Urbana-Champaign, United States
Duration: Jun 2 2019Jun 6 2019

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
Volume2019-June
ISSN (Print)1552-5996

Conference

Conference19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019
Country/TerritoryUnited States
CityUrbana-Champaign
Period06/2/1906/6/19

Keywords

  • Desk rejection
  • Multiview clustering
  • Peer review

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