Example-based Spatial Pattern Matching

Yue Chen, Kaiyu Feng*, Gao Cong*, Han Mao Kiah

*此作品的通讯作者

科研成果: 期刊稿件会议文章同行评审

2 引用 (Scopus)

摘要

The prevalence of GPS-enabled mobile devices and location-based services yield massive volume of spatial objects where each object contains information including geographical location, name, address, category and other attributes. This paper introduces a novel type of query termed example-based spatial pattern matching (EPM) query. It takes as input a set of spatial objects, each of which is associated with one or more keywords and a location. These objects serve as an example that depicts the spatial pattern that users want to retrieve. The EPM query returns all sets of objects that match the spatial pattern. The EPM query can be used for applications like urban planning, scene recognition and similar region search. We propose an efficient algorithm and three pruning techniques to answer EPM queries. Furthermore, we provide an approximation guarantee for intermediate results of the algorithm. Our experimental evaluations on four real-world datasets demonstrate the effectiveness and efficiency of our proposed algorithm and techniques.

源语言英语
页(从-至)2572-2584
页数13
期刊Proceedings of the VLDB Endowment
15
11
DOI
出版状态已出版 - 2022
已对外发布
活动48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, 澳大利亚
期限: 5 9月 20229 9月 2022

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