Abstract
In this work, we focus on understanding what happens under the hood of HTTP traffic. We proposed a systematic approach to reconstruct users click-through patterns in web starting from raw network data. We validated the proposed method using a synthesized network traffic data set and a real-world 4G network traffic data set. The precision calculated by the proposed model is 93.7 % and the recall is 91.6 %. The experiment results on the real-world 4G network traffic data show that the click-through stream of 4G network is more deeper than that of 3G network.
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Acknowledgment
This work was supported in part by China Postdoctoral Science Foundation (Grant No. 2014M562223), Shenzhen Basic Research Project (Grant No. JCYJ20140610151856729), and Natural Science Foundation of Guangdong Province (Grant No. 2014A030310154).
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Wang, S., Shen, Y., Hu, J., Xuan, Z., Lu, Z. (2015). Hadoop-Based Analysis for Large-Scale Click-Through Patterns in 4G Network. In: Xu, K., Zhu, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2015. Lecture Notes in Computer Science(), vol 9204. Springer, Cham. https://doi.org/10.1007/978-3-319-21837-3_81
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DOI: https://doi.org/10.1007/978-3-319-21837-3_81
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