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Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret

Summary: Introduces minimum-regret ad allocation that exploits viral propagation while preventing advertisers from underreporting budgets to free-ride on network effects. Despite NP-hardness and no factor approximation, gives budget-parameterized guarantees and a scalable algorithm that outperforms baselines on four real datasets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11380
Venue
VLDB
Year
2015
Pagerank
6.9848297e-05
Overall Rank
3,966 | 72.80%
DOI
10.14778/2752939.2752944

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{aslay_vldb15,
        title = {{Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret}},
        author = {Aslay, Cigdem and Lu, Wei and Bonchi, Francesco and Goyal, Amit and Lakshmanan, Laks V.S.},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {7},
        pages = {814--825},
        doi = {10.14778/2752939.2752944},
        url = {https://doi.org/10.14778/2752939.2752944},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 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
296 A Data-Based Approach to Social Influence Maximization 2012 VLDB 0.00022220351
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