論文

2018年

The Influence Maximization Problem in the Network Under Node Personalized Characteristics

2018 16TH IEEE INT CONF ON DEPENDABLE, AUTONOM AND SECURE COMP, 16TH IEEE INT CONF ON PERVAS INTELLIGENCE AND COMP, 4TH IEEE INT CONF ON BIG DATA INTELLIGENCE AND COMP, 3RD IEEE CYBER SCI AND TECHNOL CONGRESS (DASC/PICOM/DATACOM/CYBERSCITECH)
  • Weimin Li
  • ,
  • Jun Mo
  • ,
  • Yue Liu
  • ,
  • Nobuyasu Ito
  • ,
  • Yohsuke Murase
  • ,
  • Jianwei Liu

開始ページ
216
終了ページ
221
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00046
出版者・発行元
IEEE

Considering the personalization of nodes in complex networks, we propose an algorithm that maximizes the influence of similarity based on overlapping nodes and nodes. In the proposed algorithm, we investigate the overlapping of communities in the network and use overlapped nodes as the initial propagation seed set. Then, we discuss the personalized characteristics of nodes and introduce the concept of sparse attributes. An improved independent cascaded model is built to integrate the similarity of node attributes. Finally, experiments are performed on real data sets. The results show that the proposed algorithm is better than others.


リンク情報
DOI
https://doi.org/10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00046
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000450146600031&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00046
  • Web of Science ID : WOS:000450146600031

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