BERT-based multi-model fusion event subject extraction method

• Main Authors: LI YONGHUI, LI ZHEN, ZHAO XINGYING, QIN PEIGE, LIU HENG
• Format: Patent
• Language: Chinese; English
• Published: 09.06.2020
• Subjects: CALCULATING; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention relates to a BERT-based multi-model fusion event subject extraction method, and belongs to the technical field of data processing. The method comprises the following steps: preprocessingcrawling data to obtain a training sample and a prediction sample; performing embedding operation on the training sample and the prediction sample to obtain a training sample input sequence and a prediction sample input sequence of the BERT pre-training network; adopting a plurality of single models with different complexity based on a BERT pre-training network, utilizing a training sample inputsequence to train the single models, and optimizing network parameters; inputting the prediction sample input sequence into a plurality of trained single models, and outputting a plurality of model results; and fusing the plurality of model results to obtain a final prediction result of the prediction sample. According to the method, models with different complexities are adopted, diversificationof the models is guaranteed