Knowledge Graph Assisted Automatic Writing of NBA Sports News
JI Naye1, LIAO Longfei2, YAN Yanqin1, YU Dingguo1, ZHANG Fan1
1.Intelligent Media Institute, Communication University of Zhejiang, Hangzhou, Zhejiang 310018, China; 2.School of Software Engineering Technology, Zhejiang University, Hangzhou, Zhejiang 310058, China
Abstract：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.
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2021, Vol. 35 
