Characterizing and predicting mobile application usage

@article{Lim2016CharacterizingAP,
  title={Characterizing and predicting mobile application usage},
  author={Keun Woo Lim and Stefano Secci and Lionel Tabourier and Badis Tebbani},
  journal={Computer Communications},
  year={2016},
  volume={95},
  pages={82-94}
}
In this paper, we propose data clustering techniques to predict temporal characteristics of data consumption behavior of different mobile applications via wireless communications. While most of the research on mobile data analytics focuses on the analysis of call data records and mobility traces, our analysis concentrates on mobile application usages, to characterize them and predict their behavior. We exploit mobile application usage logs provided by a Wi-Fi local area network service provider… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 26 references

Classifying call profiles in large-scale mobile traffic datasets

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications • 2014

Exploring mobile data on smartphones from collection to analysis

2014 21st International Conference on Telecommunications (ICT) • 2014

Highly Comparative Feature-Based Time-Series Classification

IEEE Transactions on Knowledge and Data Engineering • 2014

MonSamp: A distributed SDN application for QoS monitoring

2014 Federated Conference on Computer Science and Information Systems • 2014

What Will 5G Be?

IEEE Journal on Selected Areas in Communications • 2014

Characterizing Service Providers Traffic of Mobile Internet Services in Cellular Data Network

2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics • 2013

Similar Papers

Loading similar papers…