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.


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    Title :

    Privacy-Aware QoE Evaluation


    Contributors:
    Zhou, Liang (author) / Wei, Xin (author) / Cui, Jingwu (author) / Zheng, Baoyu (author)


    Publication date :

    2017-06-01


    Size :

    233489 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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