This work explores the true user QoE according to the users' preferences and behaviors when the users know that they are being observed and concern about their privacy. We propose a systematic privacy-aware QoE evaluation scheme based on the observable user data. Firstly, we translate the subjective privacy- aware QoE evaluation problem into the objective rational user analysis procedure. Then, a novel class-level joint user classification and data cleaning strategy is proposed by frequently updating the training processes. In particular, an efficient correlation analysis and QoE model framework is constructed for online implementation. Our results reveal that the true user QoE can be precisely captured if only some conditions are satisfied even for the privacy-aware users.
Privacy-Aware QoE Evaluation
01.06.2017
233489 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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