Relation Extraction Based on Dual Attention Mechanism

• 作者: Long Sun Xue Li Yi Lu Yuan Rao
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: BIDIRECTIONAL GRU Multi-attention RELATION extraction
• 年，卷（期）: 2019,（1）
• 页码范围: 354-356
• 页数: 3页
• 分类号: C

摘要

The traditional deep learning model has problems that the longdistance dependent information cannot be learned, and the correlation between the input and output of the model is not considered. And the information processing on the sentence set is still insufficient. Aiming at the above problems, a relation extraction method combining bidirectional GRU network and multiattention mechanism is proposed. The word-level attention mechanism was used to extract the word-level features from the sentence, and the sentence-level attention mechanism was used to focus on the characteristics of sentence sets. The experimental verification in the NYT dataset was conducted. The experimental results show that the proposed method can effectively improve the F1 value of the relationship extraction.