Discovery of Fuzzy Multiple-Level Web Browsing Patterns

2005 ◽  
pp. 251-266
Author(s):  
Shyue-Liang Wang ◽  
Wei-Shuo Lo ◽  
Tzung-Pei Hong
Keyword(s):  
Multiple Level ◽  
Web Browsing

Private Web Browsing

1997 ◽  
Author(s):  
Paul F. Syverson ◽  
Michael G. Reed ◽  
David M. Goldschlag
Keyword(s):  
Web Browsing

Characterizing Embedded Web Browsing in Mobile Apps

2021 ◽  
pp. 1-1
Author(s):  
Deyu Tian ◽  
Yun Ma ◽  
Aruna Balasubramanian ◽  
Yunxin Liu ◽  
Gang Huang ◽  
...  
Keyword(s):  
Mobile Apps ◽  
Web Browsing ◽  
Embedded Web

scholarly journals Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling

2021 ◽  
Vol 48 (4) ◽  
pp. 37-40
Author(s):  
Nikolas Wehner ◽  
Michael Seufert ◽  
Joshua Schuler ◽  
Sarah Wassermann ◽  
Pedro Casas ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Recurrent Neural Networks ◽  
Quality Of Experience ◽  
Unique Feature ◽  
Time Series Modeling ◽  
Web Browsing ◽  
Large Dataset ◽  
Efficient Approximation

This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI - an efficient approximation to SI, with machinelearning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

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