Monochromatic and bichromatic ranked reverse boolean spatial keyword nearest neighbors search

Monochromatic and bichromatic ranked reverse boolean spatial keyword nearest neighbors search
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单色和双色排名反向布尔空间关键字最近邻搜索

DOI:
10.1007/s11280-016-0399-8
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发表时间:
2016
期刊:
World Wide Web: Internet and Web Information Systems (WWW Journal, CCF B类)
影响因子:
--
通讯作者:
Zhiming Cui
Zhiming Cui
中科院分区:
其他
文献类型:
--
作者:
Pengpeng Zhao;Hailing Fang;Victor S. Sheng;Zhixu Li;Jiajie Xu;Jian Wu;Zhiming Cui

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最近,数据库研究界对逆向最近邻(RkNN)查询进行了广泛的研究,该查询返回查询是其最近邻之一的每个答案。但是 RkNN 查询无法检索由空间位置和一组关键字描述的空间文本对象。因此,研究人员提出了一种 RSTkNN 查询来查找这些对象,同时考虑空间和文本相似性。然而,RSTkNN查询无法控制答案集的大小并根据对查询的影响程度进行排序。在本文中,我们提出了一种新问题排名反向布尔空间关键字最近邻查询,称为排名-RBSKNN查询,它同时考虑空间相似性和文本相关性,并返回影响程度最大的答案。我们提出一个单独的索引和一个混合索引来有效地处理此类查询。在不同的现实世界和合成数据集上的实验结果表明,我们的方法取得了更好的性能。
Recently, ReversekNearest Neighbors (RkNN) queries, returning every answer for which the query is one of itsknearest neighbors, have been extensively studied on the database research community. But the RkNN query cannot retrieve spatio-textual objects which are described by their spatial location and a set of keywords. Therefore, researchers proposed a RSTkNN query to find these objects, taking both spatial and textual similarity into consideration. However, the RSTkNN query cannot control the size of answer set and to be sorted according to the degree of influence on the query. In this paper, we propose a new problem Ranked Reverse Boolean Spatial Keyword Nearest Neighbors query called Ranked-RBSKNN query, which considers both spatial similarity and textual relevance, and returnstanswers with most degree of influence. We propose a separate index and a hybrid index to process such queries efficiently. Experimental results on different real-world and synthetic datasets show that our approaches achieve better performance.
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