Online Processing Algorithms for Influence Maximization
Summary: Proposes a novel OPIM algorithm enabling pause/resume interactions with provable guarantees, addressing the gap in interactive influence maximization. Empirically outperforms prior OPIM and offline methods on real data and extends to standard influence maximization. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jing Tang (Nanyang Technological University)
- 2. Xueyan Tang (Nanyang Technological University)
- 3. Xiaokui Xiao (National University of Singapore)
- 4. Junsong Yuan (State University of New York at Buffalo)
BibTeX Citation
@inproceedings{tang_sigmod18,
title = {{Online Processing Algorithms for Influence Maximization}},
author = {Tang, Jing and Tang, Xueyan and Xiao, Xiaokui and Yuan, Junsong},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3183749},
url = {https://dl.acm.org/doi/10.1145/3183713.3183749},
year = {2018}
}
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