论文标题
吸引力的风格二元性:学会通过解开来写引人注目的头条新闻
The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement
论文作者
论文摘要
引人注目的头条新闻是第一个触发更多点击的设备,从而在生产者和观众之间带来相互效果。生产商可以获得更多的流量和利润,读者可以访问出色的文章。当产生有吸引力的头条新闻时,重要的是要捕获有吸引力的内容,而且遵循引人注目的书面样式。在本文中,我们提出了一个基于分解的有吸引力的标题生成器(DAHG),该发电机(DAHG)生成标题,该标题捕获了以吸引人的风格来捕获有吸引力的内容。具体而言,我们首先设计了一个分离的模块,将有吸引力的原型标题的样式和内容分为潜在空间,并具有两个辅助约束,以确保两个空间确实被散布。然后,潜在内容信息用于进一步抛光文档表示形式并帮助捕获显着部分。最后,在有吸引力的风格的指导下,发电机将抛光文档作为输入来生成标题。公共Kuaibao数据集进行了广泛的实验表明,Dahg取得了最先进的性能。人类评估还表明,达格(Dahg)触发比现有模型的点击率高22%。
Eye-catching headlines function as the first device to trigger more clicks, bringing reciprocal effect between producers and viewers. Producers can obtain more traffic and profits, and readers can have access to outstanding articles. When generating attractive headlines, it is important to not only capture the attractive content but also follow an eye-catching written style. In this paper, we propose a Disentanglement-based Attractive Headline Generator (DAHG) that generates headline which captures the attractive content following the attractive style. Concretely, we first devise a disentanglement module to divide the style and content of an attractive prototype headline into latent spaces, with two auxiliary constraints to ensure the two spaces are indeed disentangled. The latent content information is then used to further polish the document representation and help capture the salient part. Finally, the generator takes the polished document as input to generate headline under the guidance of the attractive style. Extensive experiments on the public Kuaibao dataset show that DAHG achieves state-of-the-art performance. Human evaluation also demonstrates that DAHG triggers 22% more clicks than existing models.