Predicting the Next Location Change and Time of Change for Mobile Phone Users

Ozer M., Keles I., TOROSLU İ. H., KARAGÖZ P., Ergut S.

3rd ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems (MobiGIS), Texas, United States Of America, 04 November 2014, pp.51-59 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1145/2675316.2675318
  • City: Texas
  • Country: United States Of America
  • Page Numbers: pp.51-59
  • Keywords: Sequential Pattern Mining, Location Prediction, Mobile Phone Users
  • Middle East Technical University Affiliated: Yes


Predicting the next location of people from their mobile phone logs has become an active research area. Due to two main reasons this problem is very challenging: the log data is very large and there are variety of granularity levels for specifying the spatial and the temporal attributes. In this work, we focus on predicting the next location change of the user and when this change occurs. Our method has two steps, namely clustering the spatial data into larger regions and grouping temporal data into time intervals to get higher granularity levels, and then, applying sequential pattern mining technique to extract frequent movement patterns to predict the change of the region of the user and its time frame. We have validated our results with real data obtained from one of the largest mobile phone operators in Turkey. Our results are very encouraging, and we have obtained very high accuracy results.