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

Date

2014-11-04

Author

Ozer, Mert
Keles, Ilkcan
Toroslu, İsmail Hakkı
Karagöz, Pınar
Ergut, Salih

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Sequential pattern mining, Location prediction, Mobile phone users

URI

https://hdl.handle.net/11511/33306

DOI

https://doi.org/10.1145/2675316.2675318

Collections

Department of Computer Engineering, Conference / Seminar

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Predicting the location and time of mobile phone users by using sequential pattern mining techniques Özer, Mert; Karagöz, Pınar; Toroslu, İsmail Hakkı; Department of Computer Engineering (2014) Predicting the 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 is a variety of granularity levels both for specifying the spatial and the temporal attributes, especially with low granularity level it becomes much more complicated to define common user behaviour patterns. For the location prediction problem domain, we focused on 3 sub-problems and proposed 3 different methods for...
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Citation Formats

M. Ozer, I. Keles, İ. H. Toroslu, P. Karagöz, and S. Ergut, “Predicting the Next Location Change and Time of Change for Mobile Phone Users,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/33306.