Location Prediction of Mobile Phone Users Using Apriori-Based Sequence Mining with Multiple Support Thresholds

Date

2014-09-19

Author

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

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Due to the increasing use of mobile phones and their increasing capabilities, huge amount of usage and location data can be collected. Location prediction is an important task for mobile phone operators and smart city administrations to provide better services and recommendations. In this work, we propose a sequence mining based approach for location prediction of mobile phone users. More specifically, we present a modified Apriori-based sequence mining algorithm for the next location prediction, which involves use of multiple support thresholds for different levels of pattern generation process. The proposed algorithm involves a new support definition, as well. We have analyzed the behaviour of the algorithm under the change of threshold through experimental evaluation and the experiments indicate improvement in comparison to conventional Apriori-based algorithm.

Subject Keywords

Sequential pattern mining, Location prediction, Mobile phone users

URI

https://hdl.handle.net/11511/75674

DOI

https://doi.org/10.1007/978-3-319-17876-9_12

Conference Name

International Workshop on New Frontiers in Mining Complex Patterns (2014)

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

I. Keles, M. Ozer, İ. H. Toroslu, and P. Karagöz, “Location Prediction of Mobile Phone Users Using Apriori-Based Sequence Mining with Multiple Support Thresholds,” 2014, p. 179, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/75674.