【摘要】 是把一篇文档压缩成一个更短描述的过程。随着互联网数据量的增长,文档压缩技术对文本分析、数据浏览等有着重大的应用价值。但在基于序列模型的单文档单句摘要生成即标题生成领域中仍然存在数据使用率不高的问题。该文提出基于关键信息指导的标题生成算法。算法中的关键信息除了主流方法中使用的新闻首段句子之外,还包括新闻后续内容中有实质信息的句子,以及新闻中的重点词语。该算法将这些关键信息作为序列模型的输入,指导其生成标题,使得生成的标题能够覆盖更多的新闻信息。实验表明,在基于序列模型生成标题时,使用关键信息能够提升新闻标题生成的效果。更多还原

【Abstract】 Single document summarization is a process of compressing a document into a short description. For this purpose, this paper proposes a headline generation algorithm for a single document guided by the key information. In addition to the first paragraph of the news used in the mainstream method, the key information in the algorithm includes sentences with substantive information in the following contents, as well as key words in the news. The algorithm uses the key information as input of the sequence model to generate a title so that the generated headline can cover more news information. Experiments show that using key information can improve the effect of news headline generation based on sequence models.更多还原