ISGP: Influence Maximization on Dynamic Social Networks Using Influence SubGraph Propagation

Wan Jhen Wu, Shiou Chi Li, Jen Wei Huang

研究成果: Conference contribution

摘要

Most previous research on influence maximization has focused on static social networks, despite the dynamic nature of networks in the real world. The computational cost imposed by recalculating results in response to dynamic changes precludes the use of conventional updating algorithms when dealing with large-scale networks. In this study, we developed a novel approach to estimating the influence of nodes through the creation of Influence SubGraphs. We also developed methods by which to update Influence SubGraphs to overcome the problem of influence maximization in dynamic social networks. Experiment results demonstrated the efficacy of the proposed scheme, in achieving influence propagation performance comparable to that of state-of-the-art methods with far lower memory requirements and far shorter execution times.

原文English
主出版物標題2023 IEEE 10th International Conference on Data Science and Advanced Analytics, DSAA 2023 - Proceedings
編輯Yannis Manolopoulos, Zhi-Hua Zhou
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350345032
DOIs
出版狀態Published - 2023
事件10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023 - Thessaloniki, Greece
持續時間: 2023 10月 92023 10月 12

出版系列

名字2023 IEEE 10th International Conference on Data Science and Advanced Analytics, DSAA 2023 - Proceedings

Conference

Conference10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023
國家/地區Greece
城市Thessaloniki
期間23-10-0923-10-12

All Science Journal Classification (ASJC) codes

  • 資訊系統與管理
  • 統計、概率和不確定性
  • 人工智慧
  • 電腦科學應用
  • 資訊系統

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