Cluster Computing

, Volume 22, Supplement 3, pp 6031–6041 | Cite as

Access patterns mining from massive spatio-temporal data in a smart city

  • Lian Xiong
  • Xiaojun LiuEmail author
  • Daixin Guo
  • Zhihua Hu


Facing with massive spatio-temporal data, the traditional pattern mining methods fail to directly reflect the spatio-temporal correlation and transition rules of user access in a smart city. In this paper, we analyze the characteristics of spatio-temporal data, and map the history of user access requests to the spatio-temporal attribute domain. Then, we perform correlation analysis and identify variation rules for access requests by using regional meshing, association rules and ARIMA in the spatio-temporal attribute domain, for the purpose of mining user access patterns and predict the user’s access request. Experimental results show that our pattern mining algorithms is simple yet effective, and it achieves a prediction accuracy of 84.3% for access requests.


Smart city Spatio-temporal data Pattern mining Request prediction 



This project was supported by the Natural Science Fund of Hubei Province (Research on small file merging strategy for massive spatio-temporal data in smart city, 2018, Liu Xiaojun), the Scientific Research Program of Huanggang Normal University (Grant No. 201618003), the humanities and social science research project of the Ministry of Education, special project of science and technology personnel research project (No:13JDGC020), Hubei Provincial Higher Education Research Project (No: 2012376).


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Copyright information

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

Authors and Affiliations

  • Lian Xiong
    • 1
  • Xiaojun Liu
    • 2
    Email author
  • Daixin Guo
    • 3
  • Zhihua Hu
    • 2
  1. 1.School of Communication and Information TechnologyChongqing University of Posts and TelecommunicationsChongqingChina
  2. 2.School of TransportationHuanggang Normal UniversityHuanggangChina
  3. 3.Wuhan Maritime Communication Research InstituteWuhanChina

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