The similarity between words is used for word clustering. In spectral clustering algorithms, the information contained in the eigenvectors of an affinity matrix is used to detect the similarity. Compared with traditional clustering methods, spectral clustering performs much better for clustering the words especially in multidimensional vector spaces. the spectral clustering is implemented by Visual C++ and Matlab in the paper, which is applied to cluster small scale segmented Chinese corpus and large scale non-segmented Chinese corpus. good experimental results are observed and result analysis are given for spectral clustering.