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Research on Automatic Writing of Football Game News
WANG Wenchao, Lü Xueqiang, ZHANG Kai, ZHOU Jianshe
Acta Scientiarum Naturalium Universitatis Pekinensis    2018, 54 (2): 271-278.   DOI: 10.13209/j.0479-8023.2017.156
Abstract973)   HTML4)    PDF(pc) (542KB)(210)       Save

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.

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