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Weibo Information Propagation Dissemination Based on User Behavior Using ELM

机译：基于ELM的基于用户行为的微博信息传播

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摘要

Information dissemination prediction based on Weibo has been a hot topic in recent years. In order to study this, people always extract features and use machine learning algorithms to do the prediction. But there are some disadvantages. Aiming at these deficiencies, we proposed a new feature, the dependency between the Weibos involved in geographical locations and location of the user. We use ELM to predict behaviors of users. An information dissemination prediction model has also been proposed in this paper. Experimental results show that our proposed new feature is real and effective, and the model we proposed can accurately predict the scale of information dissemination. It also can be seen in the experimental results that the use of ELM significantly reduces the time, and it has a better performance than the traditional method based on SVM.
机译：基于微博的信息传播预测已成为近年来的热门话题。为了对此进行研究，人们总是提取特征并使用机器学习算法进行预测。但是有一些缺点。针对这些缺陷，我们提出了一项新功能，即微博在地理位置和用户位置之间的依赖性。我们使用ELM来预测用户的行为。本文还提出了一种信息传播预测模型。实验结果表明，本文提出的新功能是真实有效的，所提出的模型能够准确预测信息传播的规模。从实验结果还可以看出，使用ELM可以显着减少时间，并且比基于SVM的传统方法具有更好的性能。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第9期|876218.1-876218.11|共11页
  • 作者

    Liu Huilin; Li Yao;

  • 作者单位

    Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China.;

    Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China.;

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