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中文摘要：
结合矩阵分析知识，还原了实施谱聚类算法过程中的矩阵表示。发现了不同数据输入顺序使得相应的Affinity矩阵及Laplacian矩阵是相似的。这样，Laplacian矩阵的特征向量生成的矩阵γ也是相似的；而以γ的行向量作为输入数据的K-平均算法依赖于初始的κ个对象的选择。由此给出了导致谱聚类算法对数据输入顺序敏感的原因。
英文摘要：
Using tools from the matrix analysis, matrix representations of the spectral clustering algorithms was given. The corresponding matrixes getting from the different input order of the data set were similar to each other, so do the Laplacian matrixes. Then the matrixes γ whose columns were the top k eigenvectors of the Laplacian matrixes were similar to each other aiso. K-means algorithms using γ＇ s row vectors as the clustering data set was one of the initialization-dependent algorithms. Then get the reason of why spectral clustering algorithms were sensitive to the input order of data set.
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