Abstract
This paper presents a novel context-aware methodology for modelling and measuring user-perceived quality of experience (QoE) over time. In particular, we create a context-aware model for QoE modelling and measurement using dynamic Bayesian networks (DBN) and a context-aware state-space approach. The proposed model is then used to infer and determine users’ QoE in a sequential manner. We performed experimentation to validate the proposed model. The results prove that it can efficiently model, reason and measure QoE of the users’.
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Mitra, K., Zaslavsky, A., Åhlund, C. (2011). Dynamic Bayesian Networks for Sequential Quality of Experience Modelling and Measurement. In: Balandin, S., Koucheryavy, Y., Hu, H. (eds) Smart Spaces and Next Generation Wired/Wireless Networking. ruSMART NEW2AN 2011 2011. Lecture Notes in Computer Science, vol 6869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22875-9_12
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DOI: https://doi.org/10.1007/978-3-642-22875-9_12
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