Effect of class imbalance in heterogeneous network embedding: An empirical study

Volume: 14, Issue: 2, Pages: 101009 - 101009
Published: May 1, 2020
Abstract
Network science has been extensively explored in solving various bibliometrics tasks such as Co-authorship prediction, Author classification, Author clustering, Author ranking, Paper ranking, etc. While majority of the past studies exploit homogeneous bibliographic network (consists of singular type of nodes and edges), in recent past there is a surge in using heterogeneous bibliographic entities and their inter-dependencies using heterogeneous...
Paper Details
Title
Effect of class imbalance in heterogeneous network embedding: An empirical study
Published Date
May 1, 2020
Volume
14
Issue
2
Pages
101009 - 101009
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.