In a blog post, Netflix said the types of problem it is looking to solve include understanding the impact of QoE on user behaviour, determining what movies and shows to cache on the edge servers based on member viewing behaviour and improving the technical quality of the content in its catalogue using viewing data and member feedback.
Netflix said it also aimed to create a personalised streaming experience for each member, looking at algorithms that run in real-time once playback has started to determine what bitrate should be served and what server to download that content from.
“User behaviour refers to the way users interact with the Netflix service, and we use our data to both understand and predict behaviour. For example, how would a change to our product affect the number of hours that members watch?” asked Netflix.
“We need to determine a mapping function that can quantify and predict how changes in QoE metrics affect user behaviour. Why is this important? Understanding the impact of QoE on user behaviour allows us to tailor the algorithms that determine QoE and improve aspects that have significant impact on our members’ viewing and enjoyment.”
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