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22 November 2022 Tibetan named entity recognition based on BiLSTM-CRF
Yangji Jia, Kunyu Qi, Cairang Yun
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Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124750V (2022) https://doi.org/10.1117/12.2660074
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China
Abstract
According to the characteristics of Tibetan named entity itself, this paper analyzes the text characteristics and recognition difficulties of named entity, and puts forward BiLSTM-CRF model. The combination of the two models not only makes use of the advantages of bidirectional LSTM model to save context information, but also reduces the influence of CRF layer from sentence level to consider before and after annotation, so as to achieve the effect of learning from each other's strengths and complementing each other's weaknesses, which is more effective to solve the problem of Tibetan named entity recognition. The experimental results show that the proposed recognition method has good performance, and the f-value can reach 88.7%.
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Yangji Jia, Kunyu Qi, and Cairang Yun "Tibetan named entity recognition based on BiLSTM-CRF", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124750V (22 November 2022); https://doi.org/10.1117/12.2660074
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KEYWORDS
Performance modeling
Computer programming
Data modeling
Data processing
Information technology
Statistical analysis
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