PPSGen: Learning-Based Presentation Slides Generation for Academic Papers
PPSGen: Learning-Based Presentation Slides Generation for Academic Papers
复制标题
PPSGen：基于学习的学术论文演示幻灯片生成
DOI：
10.1109/tkde.2014.2359652
复制
发表时间：
2015
影响因子：
8.9
通讯作者：
Wan Xiaojun
中科院分区：
文献类型：
--
作者：
Hu Yue;Wan Xiaojun
在本文中，我们研究了一个非常具有挑战性的任务，自动生成学术论文的演示文稿幻灯片。生成的演示文稿幻灯片可以用作草稿，以帮助演示者以更快的方式准备他们的正式幻灯片。一个新的系统称为PPSGen提出来解决这个任务。该方法首先采用回归方法学习学术论文中句子的重要性得分，然后利用整数线性规划（ILP）方法通过选择和对齐关键短语和句子来生成结构良好的幻灯片。在网上收集的200对论文和幻灯片的测试集上的评估结果表明，我们提出的PPSGen系统可以生成质量更好的幻灯片。一个用户研究也说明了PPSGen有一些明显的优势，基线方法。
In this paper, we investigate a very challenging task of automatically generating presentation slides for academic papers. The generated presentation slides can be used as drafts to help the presenters prepare their formal slides in a quicker way. A novel system called PPSGen is proposed to address this task. It first employs the regression method to learn the importance scores of the sentences in an academic paper, and then exploits the integer linear programming (ILP) method to generate well-structured slides by selecting and aligning key phrases and sentences. Evaluation results on a test set of 200 pairs of papers and slides collected on the web demonstrate that our proposed PPSGen system can generate slides with better quality. A user study is also illustrated to show that PPSGen has a few evident advantages over baseline methods.