公平代价感知下依托VIKOR的二阶段影响力最大化

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中图分类号：TP301.5 文献标识码：A文章编号：1006-8228（2025）08-01-07

Fairness-Cost-Aware Two-Stage Influence Maximization Relying on VIKOR

ZhangHang，WangXiaojie，Xie Zehao

（SchoolofInformationanagementXinjiangUniersityofinanceandEconomicsUrumqiXinjiang3ona）

Abstract：InfluenceMaximization（IM）isakeyprobleminsocialnetworkanalysis，aimingtoidentifyasedsetofagivensize tomaximizethescopeof influencepropagation.Previous studies haveprimarilyfocusedonpropagation breadth whileneglecting fairness.ThispaperproposestheFaires-OrientedInfluenceMaximizationAlgorithmBasedonEvolutionaryAlgorithms（FIMVGA）. Byconstructinghre-dmensioalevaluationframeworkthatintegratespropagationbreadthfiessndfiesscost，VGA effectivelybalancespropagationbreadthandfaiess.Experimentalresultsshowthatcomparedtothebaselinalgorithms，FMVGA achievesabeterbalancebetweenpropagationbreadthandfairnesswhileconsideringfairness，therebyefectivelyrealizigthe equilibrium between the two.

Keywords：InfluenceMaximization;SocialNetworks；Fairness；Breadthof Dissemination；EvolutionaryAlgorithms

0引言

影响力最大化（InfluenceMaximization，IM）是复杂网络分析中的传播优化问题。（剩余10507字）