Abstract:

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

摘要：

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