Efficient and Effective Algorithms for Revenue Maximization in Social Advertising
Summary: Novel approximation algorithms for revenue maximization via seed selection in social advertising with advertiser budgets. Tackles exact and relaxed influence oracle settings, yielding better approximation ratios and faster computation, with empirical gains on four datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kai Han (University of Science and Technology Beijing)
- 2. Benwei Wu (University of Science and Technology Beijing)
- 3. Jing Tang (National University of Singapore)
- 4. Shuang Cui (University of Science and Technology Beijing)
- 5. Cigdem Aslay (Aarhus University)
- 6. Laks V. S. Lakshmanan (University of British Columbia)
BibTeX Citation
@inproceedings{han_sigmod21,
title = {{Efficient and Effective Algorithms for Revenue Maximization in Social Advertising}},
author = {Han, Kai and Wu, Benwei and Tang, Jing and Cui, Shuang and Aslay, Cigdem and Lakshmanan, Laks V. S.},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3459243},
url = {https://dl.acm.org/doi/10.1145/3448016.3459243},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,242 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD | 5.2993405e-05 |
| 10,809 | Efficient and Effective Algorithms for A Family of Influence Maximization Problems with A Matroid Constraint | 2025 | VLDB | 5.093636e-05 |
| 11,345 | Host Profit Maximization: Leveraging Performance Incentives and User Flexibility | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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