Influence maximization algorithm based on Gaussian propagation model
作者： WeiMin Li , Chao Yang , Zheng Li , Alex Munyole Luvembe
DOI: 10.1016/J.INS.2021.04.061
关键词:
摘要: Abstract The influence of each entity in a network is crucial index the information dissemination. Greedy maximization algorithms suffer from time efficiency and scalability issues. In contrast, heuristic improve efficiency, but they cannot guarantee accurate results. Considering this, this paper proposes Gaussian propagation model based on social networks. Multi-dimensional space modeling constructed by offset, motif, degree dimensions for simulation. This space’s circumstances are controlled some diffusion parameters. An algorithm proposed under model, uses an improved CELF to accelerate algorithm. Further, evaluates effectiveness supported theoretical proofs. Extensive experiments conducted compare series algorithms. results demonstrate that shows significant improvement both efficiency.
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