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Research on Construction Site Safety Q&A System Based on BERT

Ang Li

Ang Li

School of Computer Science and Engineering, Xi’an Technological UniversityXi’an, China
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Li, Ang
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Jianguo Wang

Jianguo Wang

Research Institute of Artificial Intelligence and Data Science, Xi’an Technological UniversityXi’an, China
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Wang, Jianguo
  
Dec 31, 2024
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Published Online: Dec 31, 2024
Page range: 75 - 83
DOI: https://doi.org/10.2478/ijanmc-2024-0039
Keywords
© 2024 Ang Li et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Unidirectional context build representation incrementally.
Unidirectional context build representation incrementally.

Figure 2.

Bidirectional context words can “see themselves”.
Bidirectional context words can “see themselves”.

Figure 3.

BERT model input diagram.
BERT model input diagram.

Figure 4.

Model architecture of BERT-based Q&A system.
Model architecture of BERT-based Q&A system.

Figure 5.

Effect of BERT with increasing model size.
Effect of BERT with increasing model size.

Figure 6.

Graphical interface of the construction site Q&A system.
Graphical interface of the construction site Q&A system.

Number of samples in the data set

Data Set Number Dataset Name
training set validation set test set
67700 47750 9975 9975

Experimental environment configuration parameters

Experimental Parameters Retrieve A Value
Learning rate 2e-5
Batch Size 16
Num of epoch 20
Length of Maxseq 128

Comparative effects of different baseline models

Modelling Evaluation Metrics
P/% R/% F1/%
LSTM 72.72 68.63 70.61
Text-CNN 73.40 70.23 71.78
BERT 80.5 80.96 81.65
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Computer Sciences, other
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