【作者】 徐忠华； 张剡； 陈玲； 柏文阳；

【Author】 XU Zhong-Hua,ZHANG Yan~+,CHEN Ling,BAI Wen-Yang State Key Laboratory of Novel Software Technology,Department of Computer Science and Technology,Nanjing University, Nanjing 210093,China

【机构】 南京大学计算机科学与技术系计算机软件新技术国家重点实验室；

【摘要】 轮廓查询在多标准决策中具有重要应用价值,研究者对于单表轮廓查询已经进行了大量工作,但在实际中,轮廓查询的属性很可能分布在多张表中,比如在数据仓库中的星型模型中。如果在多表连接之后进行轮廓查询,随着维度和元组数目的增加,计算代价会越来越大。为此,本文针对数据仓库中星型模型的数据特点,提出了三种此模型下的多表连接轮廓查询算法并对算法进行了实验比较分析。实验表明,我们的算法比先连接再做单表轮廓查询的算法更为有效,并且这三种算法在不同特点的数据集合下会表现出各自的优势。更多还原

【Abstract】 Skyline query is valuable in multi-criteria decision making.Most of the exiting work is based on single table skyline query.However,the data retrieved by users for the targeting skyline may often be stored in multiple tables,especially in star model of data warehouse.As a result,the costs on computing skylines on the joined table will be increase dramatically due to its increasing dimensionality and cardinality.Thus,we give three solutions to skyline-join in star model in data warehouse.Our experiments demonstrate that our algorithms are better than naive skyline query,and they dominate others in its own data set.更多还原