An improved link analysis based clustering ensemble method

Li-Juan Wang, Zhifeng Hao

Abstract: This paper proposes an improved link analysis based clustering ensemble method (ILCEM). ILCEM can transform binary data-cluster association matrix into real-valued matrix according to the similarity between clusters in all base clustering. The refined data-cluster association matrix can generate more information to clustering ensemble so as to improve the performance of clustering. Experimental results on three VCI datasets have shown that ILCEM is better than KMC, base clustering method and CSM+GKMC.