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The effect of quality metrics on the user watching behaviour in media content broadcast
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
2016 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Understanding the effects of quality metrics on the user behavior is important for the increasing number of content providers in order to maintain a competitive edge. The two data sets used are gathered from a provider of live streaming and a provider of video on demand streaming. The important quality and non quality features are determined by using both correlation metrics and relative importance determined by machine learning methods. A model that can predict and simulate the user behavior is developed and tested. A time series model, machine learning model and a combination of both are compared. Results indicate that both quality features and non quality features are important in understanding user behavior, and the importance of quality features are reduced over time. For short prediction times the model using quality features is performing slightly better than the model not using quality features.

Place, publisher, year, edition, pages
UPTEC F, ISSN 1401-5757 ; 16048
Keyword [en]
BigData, Analytics, Machine Learning, Time Series Analysis, QoE, Media Broadcast
National Category
Mathematical Analysis
URN: urn:nbn:se:uu:diva-304514OAI: diva2:1033169
External cooperation
Educational program
Master Programme in Engineering Physics
Available from: 2016-10-06 Created: 2016-10-05 Last updated: 2016-10-06Bibliographically approved

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Mathematical Analysis

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