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Continuous spatial keyword query processing over geo-textual data streams

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Abstract

Real-time processing of spatial keyword queries has been playing an indispensable role in location-based services. In this light, we propose and study a novel problem of processing continuous spatial keyword queries over geo-textual data streams. We define a new location-based continuously query that enable users to define personalized spatial requirement and textual requirement. Each query continuously feeds users with geo-textual objects that satisfy both spatial and textual requirements set by the query. To process massive-scale continuous spatial keyword queries efficiently, we develop a Continuous Spatial Keyword Query Matching (CSKQM) framework that takes a stream of queries as input and applies hierarchical dynamic grid cells to index each batch of queries. We also propose effective index update algorithm and efficient geo-textual object matching algorithm to process massive-scale continuous spatial keyword queries simultaneously over a stream of geo-textual objects. We conduct comprehensive experimental study on two real datasets to verify the performance of the CSKQM framework.

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Acknowledgements

The work is supported by the National Natural Science Foundation of China (Grant No. 61972077), LiaoNing Revitalization Talents Program (Grant No. XLYC2007079), the Science and Technology Plan Project of Shen Fu Reform and Innovation demonstration Zone in 2021 (Big Data Deep Analysis Platform for New Energy Vehicles).

Funding

The work is supported by the National Natural Science Foundation of China (Grant No. 61972077), LiaoNing Revitalization Talents Program (Grant No. XLYC2007079), the Science and Technology Plan Project of Shen Fu Reform and Innovation demonstration Zone in 2021 (Big Data Deep Analysis Platform for New Energy Vehicles).

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Authors and Affiliations

  1. College of Computer Science and Engineering, Northeastern University, Shenyang, China

    Hongwei Liu & Yongjiao Sun

  2. College of Computer Science and Engineering, Beijing Institute of Technology, Beijing, China

    Guoren Wang

Authors
  1. Hongwei Liu
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  2. Yongjiao Sun
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  3. Guoren Wang
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Contributions

Hongwei Liu: Algorithm design and development, and paper writing

Yongjiao Sun: Experimental study

Guoren Wang: Algorithm design, and paper proofreading

All authors reviewed the manuscript.

Corresponding authors

Correspondence to Hongwei Liu or Yongjiao Sun.

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Liu, H., Sun, Y. & Wang, G. Continuous spatial keyword query processing over geo-textual data streams. World Wide Web 26, 889–903 (2023). https://doi.org/10.1007/s11280-022-01062-x

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