Clustering ensemble algorithm based on prior knowledge and spectral analysis
基于先验信息和谱分析的聚类融合算法

The prior knowledge can improve clustering performance, but few of clustering ensemble algorithms consider the prior knowledge of the datasets. This paper proposed a clustering ensemble algorithm based on prior knowledge and spectral analysis. It incorporated the pairwise constraints into the spectral clustering algorithm to generate clustering members. And obtained the final result by using the combining method of co-association matrix. The experimental results demonstrate that the proposed method can efficiently improve the clustering performance.