k支配能力排序轮廓查询算法

随着轮廓查询应用的扩展,轮廓查询被扩展为其他更复杂的查询问题,包括k支配轮廓、reverse轮廓、k最多支配轮廓等等.然而,现存的轮廓查询不符合某些用户需求,还需要研究新的轮廓查询及其相关算法.为了满足用户需求,提出k支配能力轮廓的概念,同时提出一种快速的k支配能力排序轮廓查询算法(KRA).由于不确定性数据带有概率,KRA算法不能直接应用于不确定性数据.针对不确定性轮廓查询的特点,提出不确定性k支配能力轮廓的概念,并提出不确定性k支配能力排序轮廓查询算法(KRA_U).实验结果表明,算法KRA和KRA_U均可以高效地计算出k支配能力轮廓.

The k-Dominating Ranking Skyline Algorithm

With the expansion of skyline query applications,skyline has been extended in different directions,such as k-dominant skyline,reverse skyline,and k-dominating skyline,etc.For meeting the demand of some users.the concept of k-dominating skyline and an efficient k-dominating ranking skyline algorithm(KRA)are proposed.KRA could not be applied to uncertain data directly because uncertain data has probability.Based on the characteristics of skyline query on uncertain data,the concept of k-dominating skyline on uncertain data and the k-dominating ranking skyl ine algorithm on uncertain data(KRA-U)are proposed.The experimental results show that KRA and KRA-U can calculate the k-dominating ranking skyline efficiently.