帮助新闻编辑写出更好的标题：提高新闻标题关键词内容和可共享性的建议
Helping News Editors Write Better Headlines: A Recommender to Improve the Keyword Contents & Shareability of News Headlines
摘要：
我们提出了一个软件工具，采用最先进的自然语言处理（NLP）和机器学习技术，以帮助报纸编辑撰写有效的标题在线出版。该系统识别新闻文章中最突出的关键字，并根据其整体受欢迎程度和与文章的直接相关性对其进行排名。该系统还使用监督回归模型来识别可能在社交媒体上广泛分享的标题。设计用户界面的目的是简化和加快编辑对标题组成的决定过程。因此，该工具提供了一种有效的方法，将参与度和搜索引擎优化（SEO）的自动预测器的好处与对整体标题质量的人工判断相结合。
英文摘要：
We present a software tool that employs state-of-the-art natural language processing (NLP) and machine learning techniques to help newspaper editors compose effective headlines for online publication. The system identifies the most salient keywords in a news article and ranks them based on both their overall popularity and their direct relevance to the article. The system also uses a supervised regression model to identify headlines that are likely to be widely shared on social media. The user interface is designed to simplify and speed the editor's decision process on the composition of the headline. As such, the tool provides an efficient way to combine the benefits of automated predictors of engagement and search-engine optimization (SEO) with human judgments of overall headline quality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
