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Multilingual Viewpoint Detection from news comments

机译:新闻评论中的多语言观点检测

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In this paper, we investigate the task of Multilingual Viewpoint Detection (MVD) on multilingual news reader comments. To tackle the MVD task, we propose a new probabilistic graphical model called VDMC to discover latent common viewpoints from multilingual news reader comments. Our VDMC model can cope with the language gap and detect common multilingual viewpoints. To learn the model parameters, we incorporate bilingual constraints into the variational Expectation-Maximization (EM) method. Experimental results show that our VDMC model can resolve the MVD task effectively and outperform the state-of-the-art method.
机译:在本文中,我们调查了多语言观测检测(MVD)对多语言新闻读者评论的任务。为了解决MVD任务,我们提出了一个名为VDMC的新的概率图形模型,以发现来自多语言新闻读者评论的潜在共同视点。我们的VDMC模型可以应对语言差距并检测常见的多语言观点。要了解模型参数,我们将双语限制纳入变分期 - 最大化(EM)方法。实验结果表明,我们的VDMC模型可以有效地解决MVD任务,优于最先进的方法。

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