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A Novel Variable Order Markov Model Based Wireless Service Prediction Algorithm with User Similarity

机译:一种基于用户相似度的基于变阶马尔可夫模型的无线服务预测算法

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摘要

More and more researches focus on wireless service prediction problems with the rapid development of wireless network technology. It is necessary to investigate user service behaviors to improve user QoE. Therefore, in this paper, a wireless service prediction algorithm based on variable order Markov model is proposed to predict user service behaviors in wireless networks. In this algorithm, firstly, a user clustering method with user similarity is presented to categorize users. Then, a variable order Markov model based on Probabilistic Suffix Tree (PST) is introduced to predict the future service states of users. Finally, an adaptive fusion method of prediction values is given to improve the prediction accuracy. Simulation results show the effectiveness of the proposed algorithm.
机译:随着无线网络技术的飞速发展,越来越多的研究集中在无线服务预测问题上。有必要调查用户服务行为以提高用户QoE。因此,本文提出了一种基于变阶马尔可夫模型的无线服务预测算法,用于预测无线网络中的用户服务行为。在该算法中,首先提出了一种具有用户相似度的用户聚类方法对用户进行分类。然后,引入了基于概率后缀树(PST)的变阶马尔可夫模型来预测用户的未来服务状态。最后,给出了预测值的自适应融合方法,以提高预测精度。仿真结果表明了该算法的有效性。

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