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- W4308586647 abstract "Abstract In complex networks, key nodes are important factors affecting the network structure and function. Accurate mining and identifying key nodes can help people better control and utilize complex networks. In this paper, We report an accurate and efficient algorithm for critical node mining, Exploring Influential Nodes Using Global and Local Information (GLI), for the existing key node identification method that only considers local information or local information. The method of node influence includes two parts: global influence and local influence. Global influence is determined by the K-shell hierarchical information of the node. Local influence is determined jointly by the number of edges connected by the node, and the given values of the adjacent nodes. where the given values of the adjacent nodes is determined by the degree and K-shell hierarchical information. while introducing the similarity coefficient of neighbors. The proposed method solves the problems of high global algorithm complexity and low accuracy of local algorithms. The simulation experiment takes the SIR model as the reference, ten typical network models were selected as datasets, Comparing the GLI algorithm to typical algorithms at different periods, The results show that GLI effectively solves the problems of high complexity of global algorithm and low accuracy of local algorithm." @default.
- W4308586647 created "2022-11-12" @default.
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- W4308586647 date "2022-11-08" @default.
- W4308586647 modified "2023-10-18" @default.
- W4308586647 title "Exploring Influential nodes Using Global and Local Information" @default.
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- W4308586647 doi "https://doi.org/10.21203/rs.3.rs-2199249/v1" @default.
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