向量矩阵迭代自组织XML辅助聚类算法

为了提高海量XML文档集的聚类质量,提出了一种基于向量空间模型的矩阵迭代自组织XML辅助聚类算法。该算法以XML键为基础,把XML文档转化为向量矩阵,通过矩阵迭代自组织学习对XML文档实施取消、分裂与合并等优化措施。为了加速算法的收敛性,在算法中引入辅助策略,虽然不一定达到矩阵向量分类间隔最大化的目标,却在尽可能分类的情况下使得运算时间缩短,其XML键权重调整更有利聚类效果。对比其它向量聚类算法,一系列仿真实验表明所提出算法具有一定的有效性及合理性。

Vector matrix iterative self-organizing assistant clustering algorithm of XML documents

Improved the clustering quality of the massive extensible markup language(XML) document set,a vector matrix iterative self-organizing assistant clustering algorithm of XML documents(VMISACAX) is proposed.Bases on the XML key,the algorithm transforms the XML document into a vector matrix and carries out the optimizations of canceling,dissociating and uniting etc.In order to improve the convergence of the algorithm,a assistant strategy is imported to shorten the algorithm time under settling for clustering,to obtain the best result of clustering by XML key's weights,but it doesn't always obtain the maximum distance's target of matrix vector clustering.Contrasted with other vector clustering algorithms,a series of emulation experiments show that this algorithm has proper effectiveness and feasibility.