中文摘要：

在分析谱聚类实现思路和已有算法基础上，对规范切判据，最小最大切判据和自动确定聚类数目的谱聚类典型算法进行了研究和应用，通过理论分析算法各自实现机理的联系与区别，讨论它们各自的聚类特点，并利用UCI（University of California，Irvine）机器学习数据集试验对比了三种算法的聚类效果。发现谱聚类算法实现数据聚类的有效性，以及参数及相似度度量对算法性能有很大影响，在此基础上提出了算法用于解决可建模为模式识别的工程问题的可行思路，为工程实践提供了借鉴。

英文摘要：

Based on the analysis of the realizing process of spectral clustering and the existing algorithms, three typical spectral clustering methods, such as Normalized cut, Min-max cut and automatic determination the number of clusters, were selected to discuss. The respective realization mechanism and clustering features were analyzed, and the experiment results of UCI （University of California, Irvine） data sets were compared. The research results show the clustering validity of the three algorithms and indicate the effect of threshold parameter and similarity measurement on performance of algorithms. Based on this, the feasible thoughts of spectral clustering to solve practical problems were introduced. That may be reference for engineering practice.