HEMI: Hyperedge Majority Influence Maximization

June 16, 2016 Β· Declared Dead Β· πŸ› SocInf@IJCAI

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Authors Varun Gangal, Balaraman Ravindran, Ramasuri Narayanam arXiv ID 1606.05065 Category cs.SI: Social & Info Networks Cross-listed physics.soc-ph Citations 4 Venue SocInf@IJCAI Last Checked 3 months ago
Abstract
In this work, we consider the problem of influence maximization on a hypergraph. We first extend the Independent Cascade (IC) model to hypergraphs, and prove that the traditional influence maximization problem remains submodular. We then present a variant of the influence maximization problem (HEMI) where one seeks to maximize the number of hyperedges, a majority of whose nodes are influenced. We prove that HEMI is non-submodular under the diffusion model proposed.
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