【摘要】 面向体育比赛的大规模直播脚本快速及时地反映了比赛的实时进程,但依靠体育新闻记者来据此人工撰写新闻报道往往耗时费力。鉴于此,该文提出了一种自动生成体育直播脚本所对应的体育新闻的神经网络模型,该模型在一定程度上避免了传统模型过于依赖人工选择特征的局限性,同时还能综合考虑脚本中句子级局部信息与全局信息以及句子和新闻内容间的语义关联性,从而实现联合建模下的体育新闻生成。在公开数据集上的实验结果验证了该文所提方法的可行性和有效性。此外,还尝试了基于规则和模板来自动生成体育新闻的标题以突显新闻正文的关键内容。更多还原

【Abstract】 It is often time-consuming and laborious for a journalist to write sports news.In this paper,we propose a neural network model to automatically generate the sports news on the basis of the sports live scripts.The model avoids the manual feature extraction.Besides,it can also consider sentence-level information and global information within the script as well as the semantic relevance between sentences and corresponding news content in the scripts.The experimental results on the open data set verify the feasibility and effectiveness of the proposed method.In addition,we also try to generate the title of sports news based on rules and templates to extract the key content of it.更多还原