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PQRS: Prediction of Applications Based on Cellular Network Traffic with Consideration of SNS Notification

Published: 08 October 2018 Publication History

Abstract

Nowadays many people rely on smartphones in their daily lives for chatting in SNS, voice communications, searching for shopping information, and watching video contents, etc. We tried to predict the used application on a smartphone based on Call Detail Records (CDRs) in our previous work[2]. However, we have found that classification of small messages into SNS messages or simple Web browsing is difficult. In this work, we focus on enhancing the possibility of predicting the SNS messages by extracting the notification to receivers of SNS messaging before the receivers actually access to the message body. We have conducted a small experiment to distinguish the SNS notifications from short background messages in Android. The result has shown that F_1 score is 0.87

References

[1]
S. Dai, A. Nucci, D.Song A. Tongaonkar, and X. Wang, "NetworkProfiler: Towards automatic fingerprinting of Android apps," Proc. IEEE INFOCOM, pp. 809--817, 2013.
[2]
H. Ishizuka, G. Lopez, N. Mizumura, K. N. Nkurikiyeyezu, and Y. Tobe, "Smartphone application usage prediction using cellular network traffic", PerFoT'18 in conjunction with IEEE PerCom, Mar. 2018.
[3]
Z. Li, -y. Li, X. Y. Liu, W. Wang, C. Wilson, T. Xu, B. Y. Zhao, and X. Zhong "Exploring Cross-Application Cellular Traffic Optimization with Baidu TrafficGuard," in Proc. 13th Usenix Conf. Networked Syst. Des. Implement., Berkeley: USENIX Association, 2016, pp. 61--76.

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  1. PQRS: Prediction of Applications Based on Cellular Network Traffic with Consideration of SNS Notification

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        cover image ACM Conferences
        UbiComp '18: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
        October 2018
        1881 pages
        ISBN:9781450359665
        DOI:10.1145/3267305
        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Published: 08 October 2018

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        Author Tags

        1. Call Detail Record (CDR)
        2. cellular network planning
        3. kernel method
        4. support vector machine

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