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

doi:10.3233/IDA-173400

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

Information Systems WSK&I

Research output: Contribution to journal › Article › Academic › peer-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 language	English
Pages (from-to)	439-462
Number of pages	24
Journal	Intelligent Data Analysis
Volume	22
Issue number	2
DOIs	https://doi.org/10.3233/IDA-173400
Publication status	Published - 14 Mar 2018

Keywords

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

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

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.",

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AU - Yu, Hongtao

AU - Zhang, Jianpeng

AU - Liu, Shuxin

AU - Huang, Ruiyang

AU - Li, Peng

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AB - 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.

KW - Evaluation of communities

KW - link prediction

KW - modularity evaluation

KW - USI model

KW - USI-AUC criterion

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