TY - CPAPER
AU - Wei Zhou
AU - Hongjie Li
AU - Jing Yang
AU - Jinghao Fang
AB - By observing many intangible cultural heritage names, it is found that although the frequency of occurrence of these names is relatively low, they are often composed of multiple high-frequency words. Further analysis of the parts-of-speech distribution of these high-frequency words shows that there is a certain regularity. Consequently, a named entity recognition model based on POS tagging was presented in this study. By including the POS into the word vector, the word vector s information was increased and the name recognition accuracy for intangible cultural assets was enhanced. Compared with BERT-BiLSTM-CRF, the F1 score of the proposed model in the name recognition task of intangible cultural heritage items is increased from 0.854 to 0.933, an increase of 0.079.
C2 - 2024 5TH International Conference on Artificial In℡Ligence and Computer Engineering, ICAICE
DO - 10.1109/ICAICE63571.2024.10864374
N2 - By observing many intangible cultural heritage names, it is found that although the frequency of occurrence of these names is relatively low, they are often composed of multiple high-frequency words. Further analysis of the parts-of-speech distribution of these high-frequency words shows that there is a certain regularity. Consequently, a named entity recognition model based on POS tagging was presented in this study. By including the POS into the word vector, the word vector s information was increased and the name recognition accuracy for intangible cultural assets was enhanced. Compared with BERT-BiLSTM-CRF, the F1 score of the proposed model in the name recognition task of intangible cultural heritage items is increased from 0.854 to 0.933, an increase of 0.079.
SN - 979-8-3315-2891-1; 979-8-3315-2892-8
SP - 135
EP - 141
TI - Named Entity Recognition of Chinese Intangible Cultural Names Based on Part-of-Speech Tagging
ER -