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1. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF | |||
ZHANG Zhiqing,TAO Zekui | |||
Computer Science and Technology 04 January 2024 | |||
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Abstract:In order to realize the effective docking between schools and enterprises in industry-university-research cooperation projects and accurately obtain the technical needs of enterprises, based on the characteristics of concise and diversified texts of industry-university-research projects, a Chinese named entity extraction method based on BERT+BiLSTM+CRF model was proposed. Firstly, the BERT model is used to encode the input text, then the BiLSTM model is used to model the context to capture more comprehensive context information, and finally the label decoding is carried out through the CRF layer to obtain the optimal entity annotation results. Experimental results show that the proposed method is effective and feasible, and the extraction effect is better than that of the traditional method, which provides the possibility to solve the difficulties of technical demand information extraction, such as polysemy and language variants. | |||
TO cite this article:ZHANG Zhiqing,TAO Zekui. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF[OL].[ 4 January 2024] http://en.paper.edu.cn/en_releasepaper/content/4761868 |
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