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PISTIS: A Conflict of Interest Declaration and Detection System for Peer Review Management

Published: 27 May 2018 Publication History

Abstract

Detecting conflicts of interest (COIs) is key for guaranteeing the fairness of a peer-review process. In many conference management systems, the COIs of authors and reviewers are self-declared, and the declaration process is time consuming and potentially incomplete. To address this problem, we demonstrate a novel interactive system called PISTIS that assists the declaration process in a semi-automatic manner. Apart from keyword search and simple filtering, our system provides an interactive graphical interface that helps users explore potential COIs based on the heterogenous data sources. To simply the process of declaration, we also recommend latent COIs using a supervised ranking model that can be iteratively refined from the data collected from past declarations. We believe that PISTIS can be useful as an assistant tool in many real world conference management systems.

References

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Cited By

View all
  • (2024)Multi-objective optimization for assigning reviewers to proposals based on social networksJournal of Management Science and Engineering10.1016/j.jmse.2024.05.001Online publication date: Jun-2024
  • (2022)What have we learned from OpenReview?World Wide Web10.1007/s11280-022-01109-z26:2(683-708)Online publication date: 9-Nov-2022
  • (2019)Resolving Conflict of Interests and Recommending Expert Reviewers for Academic Publications Using Linked Open Data2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS.2019.8931826(91-98)Online publication date: Oct-2019
  • Show More Cited By

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Published In

cover image ACM Conferences
SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data
May 2018
1874 pages
ISBN:9781450347037
DOI:10.1145/3183713
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2018

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Author Tags

  1. conflict of interest
  2. heterogeneous network
  3. peer review process

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  • Research-article

Funding Sources

  • NSF
  • NSFC
  • UMAC Research Committee

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SIGMOD/PODS '18
Sponsor:

Acceptance Rates

SIGMOD '18 Paper Acceptance Rate 90 of 461 submissions, 20%;
Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all
  • (2024)Multi-objective optimization for assigning reviewers to proposals based on social networksJournal of Management Science and Engineering10.1016/j.jmse.2024.05.001Online publication date: Jun-2024
  • (2022)What have we learned from OpenReview?World Wide Web10.1007/s11280-022-01109-z26:2(683-708)Online publication date: 9-Nov-2022
  • (2019)Resolving Conflict of Interests and Recommending Expert Reviewers for Academic Publications Using Linked Open Data2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)10.1109/SNAMS.2019.8931826(91-98)Online publication date: Oct-2019
  • (2019)Resolving Conflict of Interests in Recommending Reviewers for Academic Publications Using Link Prediction Techniques2019 2nd International Conference on new Trends in Computing Sciences (ICTCS)10.1109/ICTCS.2019.8923033(1-6)Online publication date: Oct-2019
  • (2018)DANTEACM SIGMOD Record10.1145/3299887.329990047:2(67-72)Online publication date: 11-Dec-2018

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