Location-Dependent Skyline Query

Baihua Zheng, Ken C. K. Lee, Wang-Chien Lee
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引用次数: 51

Abstract

Given a set of data points with both spatial coordinates and non-spatial attributes, point a location-dependently dominates point b with respect to a query point q if a is closer to q than b and meanwhile a dominates b. A location- dependent skyline query (LDSQ) issued at point q is to retrieve all the points that are not location-dependently dominated by other points with regard to q. In this paper, we focus on the query processing and result validation of LDSQ over static objects. Two algorithms, namely brute-forth and delta-scanning, are proposed. The former serves as the baseline algorithm while the latter significantly improves the performance via space pruning. We further conduct a comprehensive simulation to demonstrate the performance of proposed algorithms.
位置相关的天际线查询
给定一组数据点的空间坐标和非空间属性,a点依赖所在在b点对点查询问如果一个接近问比b同时主导b。一个位置——依赖轮廓查询(LDSQ)发布点q是检索所有的点不依赖所在由其他点对q。本文我们关注LDSQ的查询处理和结果验证静态对象。提出了野蛮攻击和增量扫描两种算法。前者作为基准算法,后者通过空间剪枝显著提高性能。我们进一步进行了全面的仿真来证明所提出算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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