Mr. Yuan Zhao Profile

Yuan Zhao

at Communication Univ of China

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Proceedings Article | 22 April 2022 Paper

Sports news relationship extraction based on BERT's BiLSTM and attention

Yuan Zhao, Yingyun Yang

Proceedings Volume 12174, 1217418 (2022) https://doi.org/10.1117/12.2628524

KEYWORDS: Data modeling, Feature extraction, Performance modeling, Machine learning, Transformers, Statistical modeling, Mining, Internet, Data processing, Computer programming

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With the development of Internet big data, how people obtain a large amount of news text information and automatically obtain the information they want from the text information is an urgent task. In order to structure and analyze a large amount of Chinese text information on the Internet, this paper proposes an entity extraction method based on the BERT pre-training model and BiLSTM with the Attention Mechanism. Aiming at the problem that the BiLSTM model can only obtain feature information at the sentence context level, but cannot obtain local feature information. In this paper, based on the BiLSTM model, a BERT feature extraction model is added to obtain word vectors containing contextual semantic information, thereby capturing global and local information. At the same time, an Attention Mechanism is added to improve the effect of the model. The model was trained on the 2018 Football World Cup dataset corpus, and it was verified that the precision, F1 value and recall rate of the model have significantly improved performance on the dataset.

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