Understanding the origin and influence of the publication's idea is critical to conducting scientific research. However, the proliferation of scientific publications makes it difficult for researchers to sort out the evolution of all relevant literature. To this end, we present IdeaReader, a machine reading system that finds out which papers are most likely to inspire or be influenced by the target publication and summarizes the ideas of these papers in natural language. Specifically, IdeaReader first clusters the references and citations (first-order or higher-order) of the target publication, and the obtained clusters are regarded as the topics that inspire or are influenced by the target publication. It then picks out the important papers from each cluster to extract the skeleton of the idea flow. Finally, IdeaReader automatically generates a literature review of the important papers in each topic. Our system can help researchers gain insight into how scientific ideas flow from the target publication's references to citations by the automatically generated survey and the visualization of idea flow.
翻译：了解该出版物思想的起源和影响对于进行科学研究至关重要。然而,科学出版物的激增使得研究人员很难对所有相关文献的演变情况进行分类。为此,我们提出“设计阅读”这一机器读取系统,它能发现哪些论文最有可能受到目标出版物的启发或影响,并以自然语言总结这些论文的想法。具体地说,“设计阅读”首先将目标出版物的引用和引用(第一顺序或更高顺序)集中起来,获得的组群被视为激发目标出版物或受其影响的专题。然后从每一组中选取重要论文,以提取思想流的骨架。最后,“设计阅读”自动生成对每个专题重要论文的文献审查。我们的系统可以帮助研究人员深入了解目标出版物引用的文献是如何从自动生成的调查和思想流的可视化中流出科学想法的。
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