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Application of TextRank Algorithm for Credibility Assessment

机译:TextRank算法在信誉评估中的应用

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In this article we examine the use of TextRank algorithm for identifying web content credibility. TextRank has come to be a widely applied method for automated text summarization. In our research we apply it to see how well does it fare in recognizing credible statements from a given corpus. So far, research into use of NLP algorithms in credibility assessment was focused more on extracting the most informative statements, or dealing with recognizing the relation between claims within a document. In our paper, we use a collection of 100 websites reviewed by human subjects in regard to their credibility, therefore allowing us to check the algorithm's performance in this task. The data collected showed that the TextRank algorithm can be used for recognizing credibility on the level of aggregated statement credibility.
机译:在本文中,我们研究了使用TextRank算法确定Web内容可信度的方法。 TextRank已成为自动文本摘要的一种广泛应用的方法。在我们的研究中,我们将其应用于观察在识别给定语料库中可靠陈述方面的表现如何。到目前为止,在信誉评估中使用NLP算法的研究更多地集中在提取信息最多的陈述,或处理识别文档中索赔之间的关系方面。在本文中,我们使用了100个网站,这些网站由人类受试者根据其信誉进行了审查,因此可以检查该算法在此任务中的性能。收集到的数据表明,TextRank算法可用于在汇总语句可信度级别上识别可信度。

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