Important node group mining algorithm based on information entropy and overlap coefficient

Leping Lin; Zhengqian Song; Ning OuYang

doi:10.1117/12.2659660

30 November 2022 Important node group mining algorithm based on information entropy and overlap coefficient

Leping Lin, Zhengqian Song, Ning OuYang

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 1245606 (2022) https://doi.org/10.1117/12.2659660
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

In large-scale social networks, rich-club phenomenon is prominent. The important nodes selected by the existing algorithms are often too clustered, and the overlapping influence between nodes leads to a poor effect of maximizing the comprehensive influence of the node group. To solve this problem, an important node group mining algorithm based on information entropy and overlap coefficient is designed inspired by iterative optimization ideas. The algorithm consists of two stages: importance initialization stage and importance adaptive iterative update stage. In the initialization stage, the information entropy is used to measure the amount of information of nodes, evaluate the local importance and global importance of nodes, and improve the accuracy of the algorithm. In the iterative update stage, the overlap coefficient is used to evaluate the influence of the currently selected most important node on its surrounding neighbors, and adaptively weaken its local importance. Through the simulation experiment of the SIR propagation model, on the four real network data, the average distance between the nodes selected by the algorithm is larger and the distribution is wider, which reduces the overlap of influence and obtains greater influence.

Citation Download Citation

Leping Lin, Zhengqian Song, and Ning OuYang "Important node group mining algorithm based on information entropy and overlap coefficient", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 1245606 (30 November 2022); https://doi.org/10.1117/12.2659660

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