%0 Journal Article
%T Object-attribute subspace with sparse feature edges detection<br>具有稀疏特征的对象—属性子空间边缘重叠区域归属算法
%A ZHU Qin
%A CHEN Hua
%A <br>祝　琴
%A 陈　华
%J 计算机应用研究
%D 2013
%I 
%X The overlapped regions among the identified objects-attributes subspaces by the traditional algorithm could influence the independence of these subspaces. In order to solve this defect, this paper developed the objects-attributes subspace edges detection algorithmOASEDAbased on K-means. It designed the objective function of edge detection, algorithm with the information of within-cluster and between-cluster, and optimized the objective function by the weight theory. In the end, experimental results on synthetic datasets demonstrate that the accuracy of the proposed algorithm.
%K high-dimensional data with high dimension sparse feature
%K object-attribute subspace
%K overlapped region among object-attribute subspace<br>具有稀疏特征的高维数据
%K 对象—属性子空间
%K 对象—属性子空间边缘重叠区域
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=51EFA6F8AD1002437F8FC08E4FF88CC6&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=CA4FD0336C81A37A&sid=A4FA325EA800C820&eid=331211A5F5616413&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=18