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基于最小社團鏈接度增量的社團結構挖掘算法

Mining algorithm of community structure based on the minimal increment of link degree of a community

  • 摘要: 針對復雜網絡社團結構挖掘算法復雜度高的問題,定義了一個衡量局部社團結構的指標,提出了一種基于最小社團鏈接度增量的社團結構挖掘算法.本算法的時間復雜度為O(kd),其中d為網絡的平均節點度數,k為搜索的節點數.為了驗證本算法的性能和計算的準確性,把本算法與一種經典的挖掘局部社團結構方法——Clauset算法,進行了比較.實驗結果表明:本算法抽取的社團結構與Clauset算法相比基本一致,但在性能上有了顯著提高.

     

    Abstract: A measure of local community structure was defined, and an mining algorithm of local community structure based on the minimal increment of link degree of a community was presented for resolving the time complexity problems of finding local community structure in complex networks. The algorithm ran in time O (kd) for general graphs, where d is the mean degree and k is the number of vertices to be explored. In order to determine its performance and calculation precision, the algorithm was compared with the classical local community identification approach, Clauset algorithm. Experimental results show that mining results of the algorithm are as effective as those of Clauset algorithm on the whole, and the algorithm is much faster than Clauset algorithm.

     

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