Maximizing influence by combining influential node identification and overlapping influence reduction

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 127568 - 127568

Опубликована: Апрель 1, 2025

Язык: Английский

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MHPD: An efficient evaluation method for influence maximization on hypergraphs

Communications in Nonlinear Science and Numerical Simulation, Год журнала: 2024, Номер 139, С. 108268 - 108268

Опубликована: Авг. 14, 2024

Язык: Английский

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Hypergraph-Based Influence Maximization in Online Social Networks

Mathematics, Год журнала: 2024, Номер 12(17), С. 2769 - 2769

Опубликована: Сен. 7, 2024

Influence maximization in online social networks is used to select a set of influential seed nodes maximize the influence spread under given diffusion model. However, most existing proposals have huge computational costs and only consider dyadic relationship between two nodes, ignoring higher-order relationships among multiple nodes. It limits applicability accuracy models real complex networks. To this end, paper, we present novel information model by introducing hypergraph theory determine jointly considering adjacent improve efficiency. We mathematically formulate problem further propose sampling greedy algorithm (HSGA) effectively In HSGA, random walk-based method Monte Carlo-based approximation are devised achieve fast calculation node influences. conduct simulation experiments on six datasets for performance evaluations. Simulation results demonstrate effectiveness efficiency HSGA has lower cost higher selection than comparison mechanisms.

Язык: Английский

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Influence Maximization in Hypergraphs Using Multi-Objective Evolutionary Algorithms

Lecture notes in computer science, Год журнала: 2024, Номер unknown, С. 217 - 235

Опубликована: Янв. 1, 2024

Язык: Английский

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