关键词: 新媒体事件, K均值, 贝叶斯网络, 分类, 隐藏节点

Abstract: To make an exact and effective classification of new media events, this paper puts forward a mixed algorithm combining K-means with Bayesian network. The algorithm firstly clusters training samples by K-means, and then classifies new media events through modified Bayesian network according to the clustering results. Hierarchy Bayesian network model built in this algorithm enables Bayesian network to get rid of local optimization in parameter learning, while the introduction of hidden nodes better meets the requirements of conditional independence assumption of Bayesian network. Experimental results show that the algorithm is effective.
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Key words: new media event, K-means, Bayesian network, classification, hidden nodes