3.3 Formal Problem Definition This study aims to solve the information coverage maximization problem in the context of hypergraph networks. We first review the ...
Apr 17, 2023 · This chapter introduces and compares different models for multicast rate regions on an abstract level and establishes submodularity as the prime ...
Apr 12, 2023 · Influence without Authority: Maximizing Information Coverage in Hypergraphs ... In this study, we formulate a novel information coverage ...
This is the source code for paper Influence without Authority: Maximizing Information Coverage in Hypergraphs [SDM'23]. Requirements. python>=3.3.7.
Jun 23, 2021 · The goal is to find the smaller set of items that can influence the whole network according to the diffusion model defined. This study ...
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Jun 3, 2022 · In this paper, we propose an adaptive degree-based heuristic algorithm, i.e., Heuristic Degree Discount (HDD), which iteratively selects nodes ...
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... Hypergraphs with Real Coefficients | Chemical hypergraphs and their associated ... Influence without Authority: Maximizing Information Coverage in Hypergraphs.
Abstract—Crowd psychology plays an important role in determining the kind of activities that a person performs. In reality in a social network ...
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Mar 23, 2024 · We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community labels and ...
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Jan 8, 2022 · Influence maximization algorithms have found tremendous success in applications such as social media viral marketing.
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