Published 2014-03-01
“…Among existing clustering
algorithms,the graph-Laplacian-based spectrum clustering
algorithm has rigorous theoretical basis and high accuracy.However,the application of this
algorithm is limited by its dependence on the prior knowledge,such as the number and the size of clusters.Based on the Jordan form of graph Laplacian,an
algorithm was proposed which can obtain the prior knowledge,and perform the primary clustering based on the eigenvalues of the Jordan form.The modularity density function of clusters was defined,and an improved spectrum clustering
algorithm with the help of the function and the primary clustering was proposed.The experiments were conducted on diverse datasets showing that,compared with the classic
algorithms such as Fast-Newman and
Girvan-Newman,the
algorithm can reach a high clustering accuracy and a fast convergence rate.…”
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