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Profit Maximization for Multiple Products in Community-Based Social Networks

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Algorithmic Aspects in Information and Management (AAIM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13513))

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Abstract

In this paper, we studies the profit maximization problem for multiple kinds of products in social networks. It is formulated as a Profit Maximization Problem for Multiple Products (PMPMP), which aims at selecting a set of seed users within the total budget B such that the total profit for k kinds of products is maximized. We introduce the community structure and assume that different kinds of products are adopted by different groups of people, and different product information spread in different communities under the IC information propagation model. We prove that the objective function satisfies the k-submodularity, and then use the multilinear extension to relax the objective function. A continuous greedy algorithm is put forward for the relaxed function, which can obtain an \(\frac{1}{2}\) approximation performance guarantee, respectively. The experimental results on two real world social network datasets show the effectiveness of the proposed continuous greedy algorithm.

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Acknowledgment

This work is supported in part by the Guangdong Basic and Applied Basic Research Foundation under Grant No. 2021A1515110321 and No. 2022A1515010611 and in part by Guangzhou Basic and Applied Basic Research Foundation under Grant No. 202201010676.

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Authors and Affiliations

  1. School of Computers, Guangdong University of Technology, Guangzhou, 510006, China

    Qiufen Ni

  2. Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, 519087, China

    Jianxiong Guo

  3. Guangdong Key Lab of AI and Multi-Modal Data Processing, BNU-HKBU United International College, Zhuhai, 519087, China

    Jianxiong Guo

Authors
  1. Qiufen Ni
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  2. Jianxiong Guo
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Correspondence to Jianxiong Guo .

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Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Qiufen Ni

  2. University of Texas at Dallas, Richardson, TX, USA

    Weili Wu

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Ni, Q., Guo, J. (2022). Profit Maximization for Multiple Products in Community-Based Social Networks. In: Ni, Q., Wu, W. (eds) Algorithmic Aspects in Information and Management. AAIM 2022. Lecture Notes in Computer Science, vol 13513. Springer, Cham. https://doi.org/10.1007/978-3-031-16081-3_19

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  • DOI: https://doi.org/10.1007/978-3-031-16081-3_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16080-6

  • Online ISBN: 978-3-031-16081-3

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