摘要： Skyline查询适用于多目标决策、数据挖掘等领域。以往的研究工作主要关注确定型数据集，少数针对不确定型数据集的研究处理的也多是离散型不确定数据。为此，定义属性呈连续型分布的不确定数据集，并给出一种针对该种数据集的Skyline查询算法，利用索引和分治思想解决其Skyline查询问题。实验结果表明，该算法可以在牺牲少量精度的情况下提高查询效率。

关键词: Skyline查询, 不确定数据, 索引结构, 正态分布, 递归, 近似

Abstract: Skyline query is used in many applications in fields as diverse as multi-objective decision, data mining and so on. Previous studies mainly focus on the static dataset. There are a few exceptions however are all aiming at uncertain dataset of discrete values. This paper introduces a new form of multi-dimensional dataset whose attributes are also uncertain but are based on normal distribution. It also proposes an algorithm which can process the Skyline query to such datasets with the help of indexing and dividing and conquering. Experimental results show this approach can efficiently perform skyline query on this type of data.

Key words: Skyline query, uncertain data, index structure, normal distribution, recursion, approximation

中图分类号: 

• TP311.13