Efficient Algorithm for Budgeted Adaptive Influence Maximization: An Incremental RR-set Update Approach

Summary: Adaptive BIM with cost-aware greedy or a single influential node achieves an expected approximation under budget. Incremental RR-set updates keep extra info to fix RR-sets, enabling reuse and scalable diffusion; experiments show better influence and faster runtime. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6773
Venue: SIGMOD
Year: 2023
Pagerank: 5.093636e-05
Overall Rank: 11,409 | 21.73%
DOI: 10.1145/3617328

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Qintian Guo (Chinese University of Hong Kong)
2. Chen Feng (Chinese University of Hong Kong)
3. Fangyuan Zhang (Chinese University of Hong Kong)
4. Sibo Wang (Chinese University of Hong Kong)

BibTeX Citation

@inproceedings{guo_sigmod23,
        title = {{Efficient Algorithm for Budgeted Adaptive Influence Maximization: An Incremental RR-set Update Approach}},
        author = {Guo, Qintian and Feng, Chen and Zhang, Fangyuan and Wang, Sibo},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3617328},
        url = {https://dl.acm.org/doi/10.1145/3617328},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,913	Efficient Approximation Algorithms for Minimum Cost Seed Selection with Probabilistic Coverage Guarantee	2024	SIGMOD	5.3483178e-05

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
194	Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency	2014	SIGMOD	0.000259047
315	Influence Maximization in Near-Linear Time: A Martingale Approach	2015	SIGMOD	0.00021436156
1,478	Online Processing Algorithms for Influence Maximization	2018	SIGMOD	0.00010651983
1,919	Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models	2016	SIGMOD	9.4850778e-05
2,320	Influence Maximization Revisited: Efficient Reverse Reachable Set Generation with Bound Tightened	2020	SIGMOD	8.7576221e-05
2,752	Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks	2020	VLDB	8.1648436e-05
3,639	Revisiting the Stop-and-Stare Algorithms for Influence Maximization	2017	VLDB	7.2335041e-05
4,795	Revenue Maximization in Incentivized Social Advertising	2017	VLDB	6.5032332e-05
4,804	Efficient Algorithms for Adaptive Influence Maximization	2018	VLDB	6.5010703e-05
5,095	Pricing Influential Nodes in Online Social Networks	2020	VLDB	6.3654556e-05
5,710	Continuous Influence Maximization: What Discounts Should We Offer to Social Network Users?	2016	SIGMOD	6.1141071e-05
5,920	Efficient Approximation Algorithms for Adaptive Seed Minimization	2019	SIGMOD	6.0418521e-05
7,810	Minimizing the Regret of an Influence Provider	2021	SIGMOD	5.5393525e-05
8,595	Maximizing Social Welfare in a Competitive Diffusion Model	2021	VLDB	5.4053095e-05

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