Journal of Software:2018.29(3):642-662

(东北大学 计算机科学与工程学院, 辽宁 沈阳 110169;白城师范学院 计算机科学学院, 吉林 白城 137000)
Nearest Neighbor Query in Road Networks
BAO Jin-Ling,WANG Bin,YANG Xiao-Chun,ZHU Huai-Jie
(School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China;School of Computer Science, Baicheng Normal College, Baicheng 137000, China)
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Received:July 31, 2017    Revised:September 05, 2017
> 中文摘要: 最近邻查询作为基于位置服务的重要支持性技术之一,引起了众多学者的广泛关注和深入研究.相对于欧式空间而言,路网环境下的最近邻查询更贴近人们的生活,有着更重要的研究意义.路网环境下庞大的数据量和复杂的数据结构,使得最近邻查询的操作代价变得非常昂贵,如何有效地提高查询效率,是研究者面临的主要挑战.对路网环境下的最近邻查询技术进行综述,分别从最近邻查询采用的索引结构和查询处理过程对现有路网环境下的最近邻查询方法进行了分析和比较,也介绍了路网环境下最近邻的变体查询技术的研究情况,最后探讨路网上最近邻查询技术未来的研究重点.
Abstract:Nearest neighbor query, as one of the building blocks of location-based service, has become a hot research topic in recent years. Compared with Euclidean space, road network is a more practical model in real applications; hence, nearest neighbor query in road network has received broader research efforts. In road network, tremendous data are generated along with sophisticated data structure, making nearest neighbor query computationally expensive. This poses a major challenge to spatial database community on its effort to effectively improve the query processing efficiency for nearest neighbor query. This work summarizes existing nearest neighbor query techniques in road network, and conducts analysis and comparison among them, from various perspectives including indexing structure and algorithm implementation. Additionally, several variants of nearest neighbor query are also summarized in this work. Finally, future research focus and trend for nearest neighbor query in road network are discussed.
文章编号:     中图分类号:TP311    文献标志码:
基金项目:国家自然科学基金(61532021,61572122);中央高校基本科研业务费专项资金(N161606002);辽宁省"百千万人才工程"经费 国家自然科学基金(61532021,61572122);中央高校基本科研业务费专项资金(N161606002);辽宁省"百千万人才工程"经费
Foundation items:National Natural Science Foundation of China (61532021, 61572122);Fundamental Research Funds for the Central Universities (N161606002);Liaoning BaiQianWan Talents Program
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BAO Jin-Ling,WANG Bin,YANG Xiao-Chun,ZHU Huai-Jie.Nearest Neighbor Query in Road Networks.Journal of Software,2018,29(3):642-662