Classification Model of New Media Events Based on Bayesian Network

doi:10.3969/j.issn.1006-2475.2014.05.015

Abstract

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

CLC Number:

TP39

SUN Lin-fang1, XU Hui2, LI Jin-hai3. Classification Model of New Media Events Based on Bayesian Network[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.05.015.

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