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A Review Expert Recommendation Method Based on Comprehensive Evaluation in Multi-Source Data

  • Beihang University
  • China Academy of Information and Communications Technology

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

Abstract

Expert recommendation plays an important role in academic peer evaluation activities, because their gradual evaluation will influence the final decision. In this paper, we propose a review expert recommendation (RER) method based on comprehensive evaluation in multi-source data. First, we use network extraction technology to collect network information and build expert profile. And then an expert field classification model is built in conjunction with the text similarity method. Finally, we establish a domain expert evaluation model to recommend experts based on the needs of the review work. Subsequently, an experiment is conducted using from real data, and the results show that our proposed scheme is effective.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Control Engineering and Artificial Intelligence, CCEAI 2021
EditorsDan Zhang
PublisherAssociation for Computing Machinery
Pages36-40
Number of pages5
ISBN (Electronic)9781450388870
DOIs
StatePublished - 14 Jan 2021
Event5th International Conference on Control Engineering and Artificial Intelligence, CCEAI 2021 - Virtual, Online, China
Duration: 14 Jan 202116 Jan 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Control Engineering and Artificial Intelligence, CCEAI 2021
Country/TerritoryChina
CityVirtual, Online
Period14/01/2116/01/21

Keywords

  • Data collection
  • Expert profile construction
  • Expertise evaluation
  • Review expert recommendation

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