XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning - Intelligence Science II Third IFIP TC 12 International Conference, ICIS 2018 Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning

Fei Long
  • Fonction : Auteur
  • PersonId : 1046630
Meixia Xu
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  • PersonId : 1046631
Yulei Li
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  • PersonId : 1046632
Zhihua Wu
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  • PersonId : 1046633

Résumé

In this paper, we propose a robot editor called XiaoA to predict the popularity of online news. A method for predicting the popularity of online news based on ensemble learning is proposed with the component learners such as support vector machine, random forest, and neural network. The page view (PV) of news article is selected as the surrogate of popularity. A document embedding method Doc2vec is used as the basic analysis tool and the topic of the news is modeled by Latent Dirichlet Allocation (LDA). Experimental results demonstrate that our robot outperforms the state of the art method on popularity prediction.
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hal-02118818 , version 1 (03-05-2019)

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Fei Long, Meixia Xu, Yulei Li, Zhihua Wu, Qiang Ling. XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning. 2nd International Conference on Intelligence Science (ICIS), Nov 2018, Beijing, China. pp.340-350, ⟨10.1007/978-3-030-01313-4_36⟩. ⟨hal-02118818⟩
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