Preliminary experiments have shown how some influence maximization algorithms can take advantages from the adoption the introduced hypergraph data structure.
Oct 7, 2018 · The Social Influence Maximization Problem in Hypergraph (SIMPH) aims to select k initially-influenced seed users in a directed hypergraph G = (V, E, P).
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This study generalizes the TSS problem on networks characterized by many-to-many relationships modeled via hypergraphs.
Jun 3, 2022 · In this paper, we propose an adaptive degree-based heuristic algorithm, i.e., Heuristic Degree Discount (HDD), which iteratively selects nodes ...
Instead, they simply transform the hypergraph into a bipartite regular graph and then apply influence maximization algorithms on the regular graph. ... ... By ...
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Influence maximization in online social networks is used to select a set of influential seed nodes to maximize the influence spread under a given diffusion ...
The goal of Influence maximization problem is to detect a set of individuals who play import roles in social networks marketing. Kempe et al. (2003) first ...
Jun 3, 2022 · In this paper, we propose an adaptive degree-based heuristic algorithm, ie, Heuristic Degree Discount (HDD), which iteratively selects nodes with low influence ...
In this paper, we describe a novel data model for online social networks based on hypergraphs. We show how an influence analysis problem can be properly ...
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Sep 12, 2024 · Influence maximization in online social networks is used to select a set of influential seed nodes to maximize the influence spread under a ...
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