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

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    3 Citations (Scopus)
    117 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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