# Automatic Extraction of Flooding Control Knowledge from Rich Literature Texts Using Deep Learning
## 3 Results
### Yearwise Distribution Analysis of Research Method Sentences  
Based on 4742 English literature texts on flood disasters, the distribution of research method sentences in the last 20 years was analyzed in this study. It was studied mainly by analyzing the number of usage method sentences, quotation method sentences, and total number of article sentences in different years. The research data included 3203 usage method sentences and 1415 quotation method sentences in the manually annotated dataset, as well as 124,196 usage method sentences and 8935 quotation method sentences obtained through batch extraction. The proportion of usage method sentences refers to the ratio of the number of usage method sentences to the total number of sentences. The annual distribution is shown in Figure 5. The blue dashed line is the trend line. The distribution of the usage method sentences can be divided into four phases. In the first phase (2000-2003), the overall trend was oscillatory, with a large range of changes. This is because of the small number of documents in this phase, and the number of usage method sentences in a single document significantly affected the overall distribution. In the second phase (2003-2007), an overall upward trend was observed with an increased number of usage method sentences in the papers, indicating an increase in the number of experimental and research papers related to flood disasters. The third phase (2007-2009) exhibited a sharp downward trend and the proportion of usage method sentences decreased significantly, indicating that there were more theoretical studies in this phase. In the fourth phase (2009-2020), there was a fluctuating increasing trend, and the proportion of usage method sentences increased, indicating that experimental and research papers were the majority. Figure 5: Yearly distribution of usage method sentences in papers. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Model** & **Acc** & **F1@0** & **F1@1** & **F1@2** & **Macro\_F1** & **Weighted\_F1** & **Loss** & **Time** \\ \hline NB & 71.94 & – & – & – & – & – & – & 1 s \\ LR & 73.82 & – & – & – & – & – & – & 1 s \\ RF & 71.40 & – & – & – & – & – & – & 1 s \\ SVM & 76.05 & – & – & – & – & – & – & 5 s \\ Bert & 77.34 & 60.00 & 54.69 & 85.68 & 66.79 & 77.37 & 0.62 & 3:17:43 \\ Bert-CNN & 79.82 & 64.81 & 56.47 & 86.97 & 69.42 & 79.51 & 0.57 & 2:45:29 \\ Bert-RNN & 73.25 & 61.21 & 53.16 & 81.36 & 65.25 & 74.55 & 0.61 & 5:24:18 \\ ERNIE & 81.29 & 67.67 & 64.37 & 87.58 & 73.21 & 81.19 & 0.58 & 2:41:54 \\ \hline \hline \end{tabular}  
* Acc: accuracy rate of sentence classification; F1@0: F1 value of the usage method sentences; F1@1: F1 value of the quotation method sentences; F1@2: F1 value of the non-research method sentences; Macro\_F1: F1 macro average; Weighted F1: weighted average of F1; Loss: loss rate; Time: time spent on model training.  
\end{table} 
Table 3: Comparative performance of various classification models. The proportion of quotation method sentences refers to the ratio of the number of quotation method sentences to the total number of sentences in an article. The annual distribution of quotation method sentences (Figure 6) can be divided into four phases. The blue dashed line is the trend line. In the first phase (2000-2002), the proportion of quotation method sentences in the entire phase was relatively small, which is also related to the small number of articles published. In the second phase (2002-2003), the proportion of quotation method sentences increased sharply, indicating that studies in this phase tended to use the existing methods. In the third phase (2003-2005), a sharp decline in the overall trend was observed, with a decrease in the proportion of quotation method sentences. The fourth phase (2005-2020) showed an overall upward trend, and the ratio of quotation method sentences continued to increase, indicating that papers at this stage were more inclined to use existing methods.