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- W3182030794 abstract "We consider the revenue maximization problem in social advertising, where a social network platform owner needs to select seed users for a group of advertisers, each with a payment budget, such that the total expected revenue that the owner gains from the advertisers by propagating their ads in the network is maximized. Previous studies on this problem show that it is intractable and present approximation algorithms. We revisit this problem from a fresh perspective and develop novel efficient approximation algorithms, both under the setting where an exact influence oracle is assumed and under one where this assumption is relaxed. Our approximation ratios significantly improve upon the previous ones. Furthermore, we empirically show, using extensive experiments on four datasets, that our algorithms considerably outperform the existing methods on both the solution quality and computation efficiency." @default.
- W3182030794 created "2021-07-19" @default.
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- W3182030794 date "2021-07-11" @default.
- W3182030794 modified "2023-09-24" @default.
- W3182030794 title "Efficient and Effective Algorithms for Revenue Maximization in Social Advertising" @default.
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- W3182030794 doi "https://doi.org/10.48550/arxiv.2107.04997" @default.
- W3182030794 hasPublicationYear "2021" @default.
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