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Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE

, , , , and . 14th International Conference on Network and Service Management (CNSM), Rome, Italy, (November 2018)

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Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management, , and . IEEE Communications Letters, 23 (7): 1145-1148 (July 2019)Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones, , and . WAIN - Workshop on AI in Networks and Distributed Systems, Toulouse, France, (November 2018)Demystifying user-based active learning for network monitoring tasks, , , , and . (2023)Two Decades of AI4NETS - AI/ML for Data Networks: Challenges & Research Directions.. NOMS, page 1-6. IEEE, (2020)Network security and anomaly detection with Big-DAMA, a big data analytics framework., , , , and . CloudNet, page 16-22. IEEE, (2017)YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points., , , , , and . EuCNC, page 1-5. IEEE, (2014)Smart Active Sampling to enhance Quality Assurance Efficiency., , , , and . CoRR, (2022)IP mining: Extracting knowledge from the dynamics of the Internet addressing space., , and . ITC, page 1-9. IEEE, (2013)Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning., , , , , and . WMNC, page 40-47. IEEE, (2021)RAL: reinforcement active learning for network traffic monitoring and analysis., , and . SIGCOMM Posters and Demos, page 55-56. ACM, (2020)