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Obtaining Reference's Topic Congruity in Indonesian Publications using Machine Learning Approach

机译:使用机器学习方法在印尼出版物中获取参考文献的主题一致性

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There are some criteria on how an article is categorized as a good article for publications. It could depend on some aspect like formatting and clarity, but mainly it depends on how the content of the article is constructed. The consistency of the topic that the article was written could show us how the authors construct the main idea in the article content. One indication that shows this consistency is congruity in the article's topic and the topic of literature or reference cited in the document listed in the bibliography. This works attempting to automate the topic detection on the article's references then obtain the congruity to the article title's topic through metadata extraction and text classification. This is done by extracting metadata of an article file to obtain all possible reference title using GROBID than classify the topic using a supervised classification model. We found that some refinements in the whole approach should be considered in the next step of this work.
机译:关于如何将文章归类为适合发布的好文章有一些标准。它可能取决于某些方面,例如格式和清晰度,但主要取决于文章内容的构造方式。文章写作主题的一致性可以向我们展示作者如何构建文章内容中的主要思想。表明这种一致性的一个迹象是,该文献的主题与参考书目中列出的文献中引用的文献或参考文献的主题是一致的。这项工作尝试自动对文章的参考文献进行主题检测,然后通过元数据提取和文本分类获得与文章标题主题的一致性。这是通过提取文章文件的元数据以使用GROBID获得所有可能的参考标题,而不是使用监督分类模型对主题进行分类来完成的。我们发现,在下一步工作中应考虑对整个方法进行一些改进。

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