摘要
针对文字直播自动摘要的新闻稿存在背景信息缺乏、难以引起读者兴趣等不足,该文提出一种NBA赛事新闻的自动生成方法。采用该文提出的关键事件抽取算法从文字直播数据中抽取事件点、匹配突出关键事件的模板来生成新闻初稿,再从构建的NBA赛事知识图谱中提取背景信息和描述重点,自动生成最终的新闻稿。该文构建并公开的NBA赛事领域知识图谱,包含3个概念类、4种关系和27个属性,共有5893个实体节点。对实验生成的新闻结果随机选取了50场赛事进行了主客观评测。评测结果表明,该文提出的融合知识图谱的新闻自动写作方法有效解决了背景信息缺乏和新闻要素嵌入问题,知识图谱的使用能明显提升所生成的新闻的质量,并可支持新闻的深度阅读。
The sports news that summarized from text broadcast often fails to capture the background information.To address this issue,this paper proposes a method for automatic generation of NBA sports news.It designs a key event extraction algorithm to match the event points in the live text broadcast,and the first draft of news will be generated with the aid of the template with the key events highlighted.The final news will be automatically generated with the combination of the background information and important description,which are extracted from the constructed NBA sports domain knowledge graph.The constructed knowledge graph database has been released publicly,including 5893 entity nodes in 3 conceptual classes,4 relationships and 27 attributes.Subjective and objective evaluation results on 50 randomly selected experimental results demonstrate the efficiency of the proposed method.
作者
吉娜烨
廖龙飞
闫燕勤
俞定国
张帆
JI Naye;LIAO Longfei;YAN Yanqin;YU Dingguo;ZHANG Fan(Intelligent Media Institute,Communication University of Zhejiang,Hangzhou,Zhejiang 310018,China;School of Software Engineering Technology,Zhejiang University,Hangzhou,Zhejiang 310058,China)
出处
《中文信息学报》
CSCD
北大核心
2021年第8期135-144,共10页
Journal of Chinese Information Processing
基金
浙江省重点研发计划项目(2019C03131)
