关键词: 关系抽取, 民航突发事件, 注意力机制, 门控循环单元（GRU）模型, 领域本体

Abstract:

To address the problem that the current accuracy of relation extraction of civil aviation emergency domain ontology is low, this paper proposes a relation extraction model based on attention mechanism and bidirectional gated recurrent unit (BiGRU). Firstly, this paper queries the pre-trained word vector matrix and maps text words into vectors. Secondly, BiGRU is constructed to obtain the context semantic information of word sequence. Thirdly, attention mechanism is introduced at word level and sentence level repectively to allocate more weights to words and sentences that are more important for semantic representation. Finally, the model is trained and optimized. Experiments are conducted on the relation extraction of civil aviation emergency domain ontology, and the results show that this model has better accuracy of the relation extraction compared with traditional methods, which verifies the validity of the model and provides new method support for the automatic learning of relation extraction of civil aviation emergency domain ontology.

Key words: relation extraction, civil aviation emergency, attention mechanism, gated recurrent unit (GRU) model, domain ontology