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《Command Information System and Technology》 2019-05
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Trend Prediction for Mega-Event Based on HC-TC-LDA

PENG Junli;GU Yu;ZHANG Zhen;GENG Xiaohang;College of Automation, Hangzhou Dianzi University;  
A trend prediction framework for mega-event based on massive public news data is proposed. Firstly, the topical news captured by the web crawlers is divided by time slices and trend levels. Then, considered above data′s characteristics of large noise and strong sparsity, a feature extraction method combined with the hierarchical clustering, the term contribution and the latent Dirichlet allocation(LDA) topic model is proposed. The words with representation are extracted as features, and the feature sets is constructed. Finally, the multinomial logistic regression method is adopted to construct a trend prediction model for mega-event. Taking the North Korean nuclear behavior prediction as an example, the performance and the validity of the framework is validated.
【Fund】: 装备发展部“十三五”预研课题资助项目
【CateGory Index】: TP391.1;G353.1
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