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In complex network graph, cut model based on edge centrality doesn't apply to overlapping community detection by minimizing the algebraic connectivity of complex networks. The problem can be resolved by calculating node Correlation coefficients. It cuts one edge at one time, which is the fastest decline in the algebraic connectivity, until to divide into two communities. When components of fielder vector is less than threshold level 'a' and the difference of node adjacent edges which belong to two groups is less than 2, correlation coefficients is calculated. This node's community can be detected by the correlation coefficients. We concluded that elapsed time by ordering matrix is less than before. The advanced cut model can be used in overlapping community detection with higher efficiency and accuracy.

No abstract