Expanding scholar labels with research similarity and co-authorship network

  • Sheng Jiaqi
  • , Xu Xin*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

[Objective] This paper tries to add more academic labels for researchers from scholarly abstracts, aiming to predict their future research interests. [Methods] First, we extracted the basic labels from abstracts with the TF-IDF method. Then, we identified researchers sharing similar academic interests and co-authoriship. Finally, we expanded the basic labels with those from similar scholars and team members. [Results] Compared with existing methods, the proposed one increased recall rate of predicting by 8.33% on average. [Limitations] Our sample size was small, and we only examined scholarly articles in one language. [Conclusions] The proposed method could predict scholars’future research interests.

Original languageEnglish
Pages (from-to)75-85
Number of pages11
JournalData Analysis and Knowledge Discovery
Volume4
Issue number8
DOIs
StatePublished - 2020

Keywords

  • Co-authorship Network
  • Label Expansion
  • Topic Similarity

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