Bidirectional LSTM-CRF models for keyword extraction in Chinese sport news
Yiqi Jiang, Tongzhou Zhao, Yue Chai, Peidong Gao · 2020
State-of-the-art methods of keyword extraction from news are based on traditional machine learning and their performances rely heavily on hand-crafted feature and domain-specific knowledge. In this paper, we propose a new character-based method for keyword extraction from Chinese sport news, which based bidirectional Long Short-Term Memory with Conditional Random Field (BILSTM-CRF). The experiments result shows that BILSTM-CRF can effectively improve the performance of keyword extraction in Chinese sport news.