AAAI 2024technical14 citations
DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)
Aryaman Rao, Parth Singh, Dinesh Kumar Vishwakarma, Mukesh Prasad
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.
BibTeX
@article{Rao_Singh_Vishwakarma_Prasad_2024, title={DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract)}, volume={38}, url={https://ojs.aaai.org/index.php/AAAI/article/view/30501}, DOI={10.1609/aaai.v38i21.30501}, abstractNote={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.}, number={21}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Rao, Aryaman and Singh, Parth and Vishwakarma, Dinesh Kumar and Prasad, Mukesh}, year={2024}, month={Mar.}, pages={23628-23630} }