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Skyline代表点的选择*

DOI: 10.16451/j.cnki.issn1003-6059.201503007, PP. 239-246

Keywords: Skyline查询,Skyline代表点,集中式环境,动态规划

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Abstract:

Skyline查询在多维决策和数据挖掘等方面发挥重要作用,然而随着数据属性维度的增大,Skyline集变得非常庞大.为克服该不足,提出Skyline代表点查询.文中提出新的评价函数改进Skyline点的得分计算方法以选择k个具有代表性的Skyline点.在二维空间提出动态规划算法(DPBA),利用覆盖圆的性质确定非代表点与代表点间的覆盖距离,迭代计算评价函数值,从而得到k个代表点;在高维空间针对NP-hard问题提出一个基于aR-tree结构的近似解决方法,遍历索引结构中的节点,通过与候选Skyline集比较判断是否被支配进行剪枝,降低计算开销.大量基于合成数据与真实数据的实验证明该算法的有效性.

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