Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2018, Vol. 54 ›› Issue (2): 271-278.DOI: 10.13209/j.0479-8023.2017.156

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Research on Automatic Writing of Football Game News

WANG Wenchao1, LÜ Xueqiang1,†, ZHANG Kai2, ZHOU Jianshe2   

  1. 1. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101
    2. Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048
  • Received:2017-06-05 Revised:2017-09-05 Online:2018-03-20 Published:2018-03-20
  • Contact: LÜ Xueqiang, E-mail: lxq(at)


王文超1, 吕学强1,†, 张凯2, 周建设2   

  1. 1. 北京信息科技大学网络文化与数字传播北京市重点实验室, 北京 100101
    2. 首都师范大学北京成像技术高精尖创新中心, 北京 100048
  • 通讯作者: 吕学强, E-mail: lxq(at)
  • 基金资助:


After analyzing the characteristics of different types of sports events, the authors propose an automatic writing method for football tournament with real-time data as data source for the first time. The real-time data is automatically annotated according to historical news, and the training set is obtained. After annotation the real-time data is modeled by convolution neural network (CNN) to automatically identify the key events in real-time data. Events in structured information are transformed into news style natural language. Experiments show that the proposed method works better than other methods, and the content is more detailed and can be easily extended to the automatic writing of other sports games.

Key words: automatic writing, football, sports news, real-time data


在分析不同类型体育赛事报道特点的基础上, 首次提出一种以实时数据作为数据源的足球赛事战报自动写作方法。该方法利用历史战报, 对实时数据进行自动标注, 得到训练集, 使用卷积神经网络(CNN)对标注后的实时数据进行建模, 自动识别实时数据中的关键事件, 将关键事件中结构化的信息生成战报风格的自然语言。实验表明, 与其他方法相比, 该方法写作效果更好, 内容更加详实, 可以很方便地扩展到其他赛事的自动写作。

关键词: 自动写作, 足球, 战报, 实时数据

CLC Number: