DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)
November 30, 2023 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
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Authors
Aryaman Rao, Parth Singh, Dinesh Kumar Vishwakarma, Mukesh Prasad
arXiv ID
2311.18676
Category
cs.SI: Social & Info Networks
Cross-listed
cs.AI
Citations
2
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
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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