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Normal Forms for XML Documents XML文档的标准表单
Pub Date : 2004-09-15 DOI: 10.1016/J.INFSOF.2004.02.004
L. Teng
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引用次数: 16
A Disk-Based Algorithm for Fast Outlier Detection in Large Datasets 基于磁盘的大型数据集离群点快速检测算法
Pub Date : 1900-01-01 DOI: 10.4018/978-1-59904-120-9.CH002
Faxin Zhao, Y. Bao, Huanliang Sun, Ge Yu
Outlier Detection is an important research issue in Data Mining,the number of cells in the cell-based disk algorithm increases exponentially.The performance of this algorithm will decrease dramatically with the increasing of the number of cell and data points.Further analysis finds that there are many empty cells that are useless to outlier detection.To overcome these shortcomings,this paper apply the CD-Tree to index non-empty cells,and cluster technique is adopted to store the data objects in the same cell into linked disk pages.Some experiments are made to test the performance of the proposed algorithms.The experimental results show that the performance of the CD-Tree based and cluster-based disk algorithms are outperformed that of the cell-based disk algorithm,and the number of dimensions processed by the proposed algorithms is higher than that of the old one.
异常点检测是数据挖掘中的一个重要研究课题,在基于细胞的磁盘算法中,细胞数量呈指数级增长。该算法的性能会随着单元数和数据点的增加而急剧下降。进一步分析发现,存在许多对离群值检测无用的空单元。为了克服这些缺点,本文采用CD-Tree对非空单元进行索引,并采用聚类技术将同一单元中的数据对象存储到链接的磁盘页面中。通过实验验证了所提算法的性能。实验结果表明,基于CD-Tree和基于簇的磁盘算法的性能优于基于cell的磁盘算法,并且所提算法处理的维数高于旧算法。
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引用次数: 0
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Mini-micro Systems
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