%0 Journal Article
%T Spectral Clustering Algorithm for Large Scale Data Set Based on Accelerating Iterative Method<br>一种基于加速迭代的大数据集谱聚类方法
%A 陈丽敏
%A 杨静
%A 张健沛
%J 计算机科学
%D 2012
%I 
%X The advantage of the traditional spectral clustering algorithm is applicable in the small scale data set. A new method was proposed in the light of the laplacian matrix characteristics. First, a new Gram matrix was reconstructed and some lies of the new matrix were needed, then the eigen-decomposition based on accelerating iterative method was solved. The calculation speed of the proposed method is very fast and the space complexity is small for large scale data set
%K Clustering
%K Spectral clustering
%K Large-scale data set
%K Accelerating iterative method
%K Laplacian matrix<br>聚类，谱聚类，大规模数据集，加速迭代法，Laplacian矩阵
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=4207430C62DE8EBEA718078A73574656&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=94C357A881DFC066&sid=9D453329DCCABB94&eid=5BC9492E1D772407&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0