首页> 外文期刊>Frontiers of computer science >k-dominant Skyline query algorithm for dynamic datasets
【24h】

k-dominant Skyline query algorithm for dynamic datasets

机译:K-Pomitant Skyline查询动态数据集的算法

获取原文
获取原文并翻译 | 示例
           

摘要

At present, most k-dominant Skyline query algorithms are oriented to static datasets, this paper proposes a k-dominant Skyline query algorithm for dynamic datasets. The algorithm is recursive circularly. First, we compute the dominant ability of each object and sort objects in descending order by dominant ability. Then, we maintain an inverted index of the dominant index by k-dominant Skyline point calculation algorithm. When the data changes, it is judged whether the update point will affect the k-dominant Skyline point set. So the k-dominant Skyline point of the new data set is obtained by inserting and deleting algorithm. The proposed algorithm resolves maintenance issue of a frequently updated database by dynamically updating the data sets.The experimental results show that the query algorithm can effectively improve query efficiency.
机译:目前,大多数K-主导的天际线查询算法面向静态数据集,提出了一种用于动态数据集的k主导地平线查询算法。算法循环递归。首先,我们通过主导能力计算每个对象的主导能力并按降序排序对象。然后,我们通过K-显性天际线点计算算法维持主导指标的倒指数。当数据发生变化时,判断更新点是否会影响k主导天际线点集。因此,通过插入和删除算法来获得新数据集的k主导地平线点。该算法通过动态更新数据集来解决频繁更新数据库的维护问题。实验结果表明查询算法可以有效地提高查询效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号