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Efficient Index-Based Approaches for Skyline Queries in Location-Based Applications

机译:基于位置的应用程序中基于天际索引的高效基于索引的方法

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摘要

Enriching many location-based applications, various new skyline queries are proposed and formulated based on the notion of locational dominance, which extends conventional one by taking objects' nearness to query positions into account additional to objects' nonspatial attributes. To answer a representative class of skyline queries for location-based applications efficiently, this paper presents two index-based approaches, namely, augmented R-tree and dominance diagram. Augmented R-tree extends R-tree by including aggregated nonspatial attributes in index nodes to enable dominance checks during index traversal. Dominance diagram is a solution-based approach, by which each object is associated with a precomputed nondominance scope wherein query points should have the corresponding object not locationally dominated by any other. Dominance diagram enables skyline queries to be evaluated via parallel and independent comparisons between nondominance scopes and query points, providing very high search efficiency. The performance of these two approaches is evaluated via empirical studies, in comparison with other possible approaches.
机译:丰富了许多基于位置的应用程序,并根据位置优势的概念提出了各种新的天际线查询,并提出了新的天际线查询,这种查询扩展了传统查询,通过考虑对象的接近性来查询位置而不是对象的非空间属性。为了有效地回答针对基于位置的应用程序的代表性的天际线查询类,本文提出了两种基于索引的方法,即增强R树和优势图。增强型R树通过在索引节点中包括聚合的非空间属性来扩展R树,从而在索引遍历期间启用优势检查。优势图是一种基于解决方案的方法,通过该方法,每个对象都与预先计算的非优势范围相关联,其中查询点应具有相应的对象,该对象在位置上不受任何其他对象的支配。利用优势图,可以通过非优势范围和查询点之间的并行和独立比较来评估天际线查询,从而提供非常高的搜索效率。与其他可能的方法相比,通过经验研究评估了这两种方法的性能。

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