USI-AUC : an evaluation criterion of community detection based on a novel link-prediction method

Yiteng Wu, Hongtao Yu, Jianpeng Zhang, Shuxin Liu, Ruiyang Huang, Peng Li

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
53 Downloads (Pure)

Abstract

Modularity Evaluation (ME) is usually used in community detection for evaluating the disjoint and overlapping communities. In this paper, two obvious defects of ME are revealed and proved, including the non-decreasing contribution of isolated nodes to modularity and lacking of appropriate measures on overlapping community. We also propose a new evaluation criterion, the USI-AUC, which is the Area Under the Curve (AUC), originated from link-prediction of Uniform-Structure-Information (USI) model. We test the new criterion on various datasets, and find that such criterion can avoid the issues exposed in ME.

Original languageEnglish
Pages (from-to)439-462
Number of pages24
JournalIntelligent Data Analysis
Volume22
Issue number2
DOIs
Publication statusPublished - 14 Mar 2018

Keywords

  • Evaluation of communities
  • link prediction
  • modularity evaluation
  • USI model
  • USI-AUC criterion

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