New Algorithm of Detecting Community Structure Based on Degree Centrality
Dividing the result for the traditional K-means algorithm is influenced by the initial central node, and each refresh center nodes need to be calculated, cause the higher algorithm running time and other issues. Proposes an improved algorithm based on centrality of K-means, CDK algorithm. The algorithm is based on the shortest path between the node and the node to the center of the central node determining the initial associations, then according to Jaccard similarity between nodes, will be divided into K non-central node in societies. CDK al-gorithm avoids the traditional K-means algorithm due to the random selection of initial results of the center divide and cause instability, poor accuracy problems, while CDK refresh algorithm when the central node without calculation, has a lower time complexity.
NETL
NSTL
万方数据
维普
