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Efficient Approximation Algorithms for Adaptive Seed Minimization

Summary: Adaptive seed minimization in social networks with batchwise feedback; ASTI exploits observed diffusion in rounds to reduce seeds. Offers (1 - (1 - 1/b)^b)(1 - 1/e)(1 - ε) approximation in expectation in O((η(m+n))/ε^2 ln n) time; first scalable adaptive guarantee, supported by experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5755
Venue
SIGMOD
Year
2019
Pagerank
6.0418521e-05
Overall Rank
5,920 | 59.39%
DOI
10.1145/3299869.3319881

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{tang_sigmod19,
        title = {{Efficient Approximation Algorithms for Adaptive Seed Minimization}},
        author = {Tang, Jing and Huang, Keke and Xiao, Xiaokui and Lakshmanan, Laks V.S. and Tang, Xueyan and Sun, Aixin and Lim, Andrew},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319881},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319881},
        year = {2019}
}

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