一种针对反向空间偏好top-k查询的高效处理方法

发布时间：2018-08-27 14:14

【摘要】：随着地理位置定位技术的蓬勃发展,基于在线位置服务技术的应用也越来越多.提出一种查询类型——反向空间偏好top-k查询.类似于传统的反向空间top-k查询,对于给定的空间查询对象,该查询返回使该对象满足top-k属性得分的那些用户.但不同的是,该对象的属性不是自身具有的特性,而是通过计算该对象与其他偏好对象之间的空间关系(如距离)而确定.这种查询在市场分析等许多重要领域具有需求,例如,根据查询结果,分析出某个地区中某个设施受欢迎的程度.但是,由于大量空间对象的存在导致对象之间空间关系的计算代价非常高,如何实时地计算出对象的空间属性得分,给查询处理带来很大的挑战.针对该问题提出优化的查询处理算法包括:数据集剪枝、数据集批量处理、基于权重的用户分组等策略.通过理论分析和充分的实验验证,证明了所提出方法的有效性.与普通方法相比,这些方法能够大幅度提高查询处理的执行时间和I/O效率.
[Abstract]:With the rapid development of geographical location technology, the application of online location service technology is more and more. A query type, reverse space preference top-k query, is proposed. Similar to the traditional reverse spatial top-k query, for a given spatial query object, the query returns those users who make the object satisfy the score of the top-k attribute. The difference is that the property of the object is not its own property, but is determined by calculating the spatial relationship between the object and other preference objects (such as distance). This kind of query has the demand in many important fields such as market analysis, for example, based on the results of the query, the popularity of a certain facility in a certain area is analyzed. However, due to the existence of a large number of spatial objects, the computation cost of spatial relations between objects is very high. How to calculate the spatial attribute score of objects in real time brings a great challenge to query processing. To solve this problem, an optimized query processing algorithm is proposed, including pruning of data sets, batch processing of data sets, user grouping based on weights and so on. The effectiveness of the proposed method is proved by theoretical analysis and sufficient experimental verification. Compared with common methods, these methods can greatly improve the execution time and I / O efficiency of query processing.
【作者单位】：东北大学计算机软件与理论研究所;东北大学计算中心;
【基金】：国家自然科学基金(61272179,61472071,61402093) 中央高校基本科研业务费专项资金(N141604001)~~
【分类号】：TP311.13

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