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Multi-objective Spatial Keyword Query with Semantics

  • Jing Chen
  • Jiajie XuEmail author
  • Chengfei Liu
  • Zhixu Li
  • An Liu
  • Zhiming Ding
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10178)

Abstract

Multi-objective spatial keyword query finds broad applications in map services nowadays. It aims to find a set of objects that can cover all query objectives and are reasonably distributed in spatial. However, existing approaches mainly take the coverage of query keywords into account, while leaving the semantics behind the textual data to be largely ignored. This limits us to return those rational results that are synonyms but morphologically different. To address this problem, this paper studies the problem of multi-objective spatial keyword query with semantics. It targets to return the object set that is optimum regarding to both spatial proximity and semantic relevance. We propose an indexing structure called LIR-tree, as well as two advanced query processing approaches to achieve efficient query processing. Empirical study based on real dataset demonstrates the good effectiveness and efficiency of our proposed algorithms.

Notes

Acknowledgement

This work was partially supported by Chinese NSFC project under grant numbers 61402312, 61232006, 61402313, 61572336, 61502324, 61572335, and Australia Research Council discovery projects under grant numbers DP140103499, DP160102412.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jing Chen
    • 1
  • Jiajie Xu
    • 1
    Email author
  • Chengfei Liu
    • 2
  • Zhixu Li
    • 1
  • An Liu
    • 1
  • Zhiming Ding
    • 3
  1. 1.Department of Computer Science and TechnologySoochow UniversitySuzhouChina
  2. 2.Faculty of SETSwinbourne University of TechnologyMelbourneAustralia
  3. 3.Department of Computer Science and TechnologyBeijing University of TechnologyBeijingChina

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