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Assessing Quality Values of Wikipedia Articles Using Implicit Positive and Negative Ratings

机译:使用内隐的正面和负面评价评估维基百科文章的质量价值

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In this paper, we propose a method to identify high-quality Wikipedia articles by mutually evaluating editors and text using implicit positive and negative ratings. One of major approaches for assessing Wikipedia articles is a text survival ratio based approach. However, the problem of this approach is that many low quality articles are misjudged as high quality, because of two issues. This is because, every editor does not always read the whole articles. Therefore, if there is a low quality text at the bottom of a long article, and the text have not seen by the other editors, then the text survives beyond many edits, and the survival ratio of the text is high. To solve this problem, we use a section or a paragraph as a unit of remaining instead of a whole page. This means that if an editor edits an article, the system treats that the editor gives positive ratings to the section or the paragraph that the editor edits. This is because, we believe that if editors edit articles, the editors may not read the whole page, but the editors should read the whole sections or paragraphs, and delete low-quality texts. From experimental evaluation, we confirmed that the proposed method could improve the accuracy of quality values for articles.
机译:在本文中,我们提出了一种方法,该方法通过使用隐含的肯定和否定评级相互评估编辑者和文本来识别高质量的维基百科文章。评估Wikipedia文章的主要方法之一是基于文本生存率的方法。然而,这种方法的问题在于,由于两个问题,许多低质量的物品被错误地判断为高质量。这是因为,每个编辑者并不总是阅读整篇文章。因此,如果长篇文章的底部有低质量的文本,并且其他编辑者看不到该文本,则该文本可以保留许多次编辑,并且生存率很高。为了解决这个问题,我们使用一个节或一个段落作为剩余单位而不是整个页面。这意味着,如果编辑者编辑文章,则系统将认为该编辑者对该编辑者所编辑的部分或段落给予正面评价。这是因为,我们认为,如果编辑者编辑文章,则编辑者可能不会阅读整个页面,但是编辑者应阅读整个部分或段落,并删除低质量的文本。通过实验评估,我们证实了该方法可以提高商品质量值的准确性。

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