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Holistic influence maximization for targeted advertisements in spatial social networks

Version 2 2024-06-05, 02:21
Version 1 2018-12-20, 18:07
conference contribution
posted on 2024-06-05, 02:21 authored by Jianxin Li, T Cai, A Mian, RH Li, T Sellis, JX Yu
The problem of influence maximization has recently received significant attention. However, most studies focused on user influence via cyber interactions while ignoring their physical interactions which are important to gauge influence propagation. Additionally, targeted campaigns or advertisements have not received sufficient attention. To do this, we first devise a novel holistic influence diffusion model and then formulate a new holistic influence maximization query problem and develop three algorithms. Finally, we conduct extensive experiments to evaluate the effectiveness and efficiency of the proposed solutions.

History

Pagination

1344-1347

Location

Paris, France

Start date

2018-04-16

End date

2018-04-19

ISBN-13

9781538655207

Notes

timestamp: Tue, 20 Nov 2018 10:20:00 +0100 biburl: https://dblp.org/rec/bib/conf/icde/LiCMLSY18 bibsource: dblp computer science bibliography, https://dblp.org

Publication classification

EN.1 Other conference paper

Title of proceedings

Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Event

2018 IEEE 34th International Conference on Data Engineering (ICDE)

Publisher

IEEE

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