Abstract
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.
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Acknowledgements
This research was supported by Ministry of Science, Industry and Technology of Turkey with project number 01256.STZ.2012-1 and title “Predicting Mobile Phone Users’ Movement Profiles”.
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Keles, I., Ozer, M., Toroslu, I.H., Karagoz, P. (2015). Location Prediction of Mobile Phone Users Using Apriori-Based Sequence Mining with Multiple Support Thresholds. In: Appice, A., Ceci, M., Loglisci, C., Manco, G., Masciari, E., Ras, Z. (eds) New Frontiers in Mining Complex Patterns. NFMCP 2014. Lecture Notes in Computer Science(), vol 8983. Springer, Cham. https://doi.org/10.1007/978-3-319-17876-9_12
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DOI: https://doi.org/10.1007/978-3-319-17876-9_12
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