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Automatic Extraction and Learning of Keyphrases from Scientific Articles

机译:从科学文章中自动提取和学习关键词

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摘要

Many academic journals and conferences require that each article include a list of keyphrases. These keyphrases should provide general information about the contents and the topics of the article. Keyphrases may save precious time for tasks such as filtering, summarization, and categorization. In this paper, we investigate automatic extraction and learning of keyphrases from scientific articles written in English. Firstly, we introduce various baseline extraction methods. Some of them, formalized by us, are very successful for academic papers. Then, we integrate these methods using different machine learning methods. The best results have been achieved by J48, an improved variant of C4.5. These results are significantly better than those achieved by previous extraction systems, regarded as the state of the art.
机译:许多学术期刊和会议都要求每篇文章都包含关键字短语列表。这些关键短语应提供有关文章内容和主题的一般信息。关键字短语可以节省诸如过滤,摘要和分类之类的任务的宝贵时间。在本文中,我们研究了用英语撰写的科学文章中关键词的自动提取和学习。首先,我们介绍各种基线提取方法。其中一些经我们正式确定的学术论文非常成功。然后,我们使用不同的机器学习方法来整合这些方法。 J48(C4.5的改进版本)已实现最佳结果。这些结果明显优于被认为是最新技术的先前提取系统所获得的结果。

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