Minimizing the Regret of an Influence Provider
Summary: Shifts influence to OOH provider, formalizing MROAM to minimize regret from unmet requests and over-provisioning. MROAM is NP-hard and inapproximable; a randomized 2-neighborhood local search yields a dual-approximation, NYC/Singapore data show ~5× gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yipeng Zhang (Royal Melbourne Institute of Technology)
- 2. Yuchen Li (Singapore Management University)
- 3. Zhifeng Bao (Royal Melbourne Institute of Technology)
- 4. Baihua Zheng (Singapore Management University)
- 5. H. V. Jagadish (University of Michigan)
BibTeX Citation
@inproceedings{zhang_sigmod21,
title = {{Minimizing the Regret of an Influence Provider}},
author = {Zhang, Yipeng and Li, Yuchen and Bao, Zhifeng and Zheng, Baihua and Jagadish, H. V.},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457257},
url = {https://dl.acm.org/doi/10.1145/3448016.3457257},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,242 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD | 5.2993405e-05 |
| 11,216 | Influence Maximization via Vertex Countering | 2024 | VLDB | 5.093636e-05 |
| 11,345 | Host Profit Maximization: Leveraging Performance Incentives and User Flexibility | 2024 | VLDB | 5.093636e-05 |
| 11,409 | Efficient Algorithm for Budgeted Adaptive Influence Maximization: An Incremental RR-set Update Approach | 2023 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 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 |
| 3,966 | Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret | 2015 | VLDB | 6.9848297e-05 |
| 4,126 | Efficient Selection of Geospatial Data on Maps for Interactive and Visualized Exploration | 2018 | SIGMOD | 6.8860475e-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 |
| 5,858 | Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model | 2019 | SIGMOD | 6.0641406e-05 |
| 13,507 | ITAA: An Intelligent Trajectory-driven Outdoor Advertising Deployment Assistant | 2019 | VLDB | - |
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|---|---|---|---|---|
| 1 | 1,919 | Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models | 2016 | SIGMOD |
| 2 | 1,478 | Online Processing Algorithms for Influence Maximization | 2018 | SIGMOD |
| 3 | 2,199 | Real-time Targeted Influence Maximization for Online Advertisements | 2015 | VLDB |
| 4 | 11,345 | Host Profit Maximization: Leveraging Performance Incentives and User Flexibility | 2024 | VLDB |
| 5 | 7,315 | Analysis of Influence Contribution in Social Advertising | 2022 | VLDB |
| 6 | 4,725 | Efficient Location-Aware Influence Maximization | 2014 | SIGMOD |
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| 8 | 9,242 | Managing Conflicting Interests of Stakeholders in Influencer Marketing | 2023 | SIGMOD |
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| 10 | 3,966 | Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret | 2015 | VLDB |