Efficient Top K Temporal Spatial Keyword Search

  • Chengyuan Zhang
  • Lei Zhu
  • Weiren Yu
  • Jun LongEmail author
  • Fang Huang
  • Hongbo Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11154)


Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale in many emerging applications such as location based services and social networks. Due to their importance, a large body of work has focused on efficiently computing various spatial keyword queries. In this paper, we study the top-k temporal spatial keyword query which considers three important constraints during the search including time, spatial proximity and textual relevance. A novel index structure, namely SSG-tree, to efficiently insert/delete spatio-temporal web objects with high rates. Base on SSG-tree an efficient algorithm is developed to support top-k temporal spatial keyword query. We show via extensive experimentation with real spatial databases that our method has increased performance over alternate techniques.



This work was supported in part by the National Natural Science Foundation of China (61702560, 61379110, 61472450), the Key Research Program of Hunan Province (2016JC2018), Natural Science Foundation of Hunan Province (2018JJ3691), and Science and Technology Plan of Hunan Province (2016JC2011).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Chengyuan Zhang
    • 1
    • 2
  • Lei Zhu
    • 1
    • 2
  • Weiren Yu
    • 3
  • Jun Long
    • 1
    • 2
    Email author
  • Fang Huang
    • 1
  • Hongbo Zhao
    • 4
  1. 1.School of Information ScienceCentral South UniversityChangshaChina
  2. 2.Big Data and Knowledge Engineering InstituteCentral South UniversityChangshaChina
  3. 3.School of Engineering and Applied ScienceAston UniversityBirminghamUK
  4. 4.School of Minerals Processing and BioengineeringCentral South UniversityChangshaChina

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