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Journal of Computer Science and Technology

, Volume 33, Issue 4, pp 697–710 | Cite as

Discovering Functional Organized Point of Interest Groups for Spatial Keyword Recommendation

  • Yan-Xia Xu
  • Wei Chen
  • Jia-Jie Xu
  • Zhi-Xu Li
  • Guan-Feng Liu
  • Lei Zhao
Regular Paper
  • 2 Downloads

Abstract

A point of interest (POI) is a specific point location that someone may find useful. With the development of urban modernization, a large number of functional organized POI groups (FOPGs), such as shopping malls, electronic malls, and snacks streets, are springing up in the city. They have a great influence on people’s lives. We aim to discover functional organized POI groups for spatial keyword recommendation because FOPGs-based recommendation is superior to POIs-based recommendation in efficiency and flexibility. To discover FOPGs, we design clustering algorithms to obtain organized POI groups (OPGs) and utilize OPGs-LDA (Latent Dirichlet Allocation) model to reveal functions of OPGs for further recommendation. To the best of our knowledge, we are the first to study functional organized POI groups which have important applications in urban planning and social marketing.

Keywords

functional organized point of interest (POI) group POI clustering OPG-LDA (organized point of interest group-latent Dirichlet allocation) model spatial keyword recommendation 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Yan-Xia Xu
    • 1
  • Wei Chen
    • 1
  • Jia-Jie Xu
    • 1
  • Zhi-Xu Li
    • 1
  • Guan-Feng Liu
    • 1
  • Lei Zhao
    • 1
  1. 1.School of Computer Science and TechnologySoochow UniversitySuzhouChina

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