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

Authors

  • Aryaman Rao Delhi Technological University
  • Parth Singh Delhi Technological University
  • Dinesh Kumar Vishwakarma Delhi Technological University
  • Mukesh Prasad University of Technology Sydney

DOI:

https://doi.org/10.1609/aaai.v38i21.30501

Keywords:

Evolutionary Computation, Optimization, Graphical Models, Applications Of AI

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.

Published

2024-03-24

How to Cite

Rao, A., Singh, P., Vishwakarma, D. K., & Prasad, M. (2024). DQSSA: A Quantum-Inspired Solution for Maximizing Influence in Online Social Networks (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23628-23630. https://doi.org/10.1609/aaai.v38i21.30501