关键词: 贝叶斯网络, 结构学习, 马尔可夫毯, 互联云, QoE评价

Abstract: The automatic learning of Bayesian network graph structure is a challenge in machine learning. Aiming at the problems of low learning efficiency of traditional algorithm， difficulty in removing redundant edges and determining the direction of the edges in the structure， a Bayesian network structure learning algorithm based on Markov blanket was proposed. The proposed algorithm improves the classical Markov blanket learning algorithm， reduces the number of conditional independent inspections， and is more suitable for Bayesian network structure learning in the subsequent determination of directed structures. At the same time， a general solution for determining the direction of two directed edges was given， which effectively improves the learning efficiency of the learning algorithm. Finally， the Bayesian network-based interconnected cloud QoE evaluation model was established， and the simulation experiment was carried out. The results showed that the improved learning algorithm is superior to the traditional algorithm in prediction accuracy and learning efficiency.

Key words: Bayesian networks, structure learning, Markov blanket, intercloud, QoE evaluation