DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)

• URL: http://arxiv.org/abs/2311.18676v1
• Date: Thu, 30 Nov 2023 16:23:44 GMT
• Title: DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)
• Authors: Aryaman Rao, Parth Singh, Dinesh Kumar Vishwakarma, Mukesh Prasad
• Abstract summary: Influence Maximization is the task of selecting optimal nodes maximising the influence spread in social networks. This study proposes a Discretized Quantum-based Salp Swarm Algorithm (DQSSA) for optimizing influence diffusion in social networks.
• Score: 17.756827206688364
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Influence Maximization is the task of selecting optimal nodes maximising the influence spread in social networks. This study proposes a Discretized Quantum-based Salp Swarm Algorithm (DQSSA) for optimizing influence diffusion in social networks. By discretizing meta-heuristic algorithms and infusing them with quantum-inspired enhancements, we address issues like premature convergence and low efficacy. The proposed method, guided by quantum principles, offers a promising solution for Influence Maximisation. Experiments on four real-world datasets reveal DQSSA's superior performance as compared to established cutting-edge algorithms.

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