## 3 Results
### Impact Analysis  
This study developed a domain-specific lexicon for terms related to emergencies in gas pipeline networks and assigned a specific weight to each term. Table 8 reused the same terms as a previous table for comparative analysis. The comparison shows increased TF-IDF values for most terms in the latter table. For example, TF-IDF values increased, such as \"construction\" from 0.87825 to 0.98185, \"production\" from 0.75127 to 0.94400, and \"installation\" from 0.61668 to 1.01146. This increase may indicate a higher frequency or greater distinctiveness of these terms in the relevant document corpus. Conversely, the TF-IDF value for \"excavator\" dropped significantly from 0.58360 to 0.23351, likely indicating a decrease in specificity or an increase in general usage within the final document collection. The TF-IDF value for \"emergency\" increased from 0.58144 to 1.17261, suggesting heightened specificity and importance. Significant increases in the TF-IDF values for \"safety\" and \"gas\" indicate a heightened focus on these concepts within the domain. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Example** & **Top\_10** & **Similar Words** & **Example** & **Top\_10** & **Similar Words** & **Example** & **Top\_10** \\ \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Example Word** & **Candidate Words** & **Example Word** & **Candidate Words** & **Example Word** & **Candidate Words** \\ \hline Construction & 0.98185 & Valve & 0.85366 & Rescue & 0.87627 \\ \hline Operation & 0.93430 & Engineering & 0.96161 & Organization & 0.88904 \\ \hline Liquefied & & & & & \\ Petroleum Gas & 0.81294 & Excavation & 0.52760 & Department & 0.85826 \\ \hline Pipeline & 0.83681 & Excavator & 0.23351 & Plan & 0.80443 \\ \hline Production & 0.94400 & Emergency & 1.17261 & Construction Site & 0.39046 \\ \hline Natural Gas & 0.97668 & Inspection & 0.91783 & Safety & 0.99905 \\ \hline Gas Pipe & 0.88607 & Deflagration & 0.42427 & Disposal & 0.90271 \\ \hline Pipeline & 1.09717 & Management & 0.85444 & Connection & 0.93137 \\ \hline Installation & 1.01146 & Explosion & 0.77161 & Pressure & 1.02946 \\ \hline Underground & 0.78267 & Construction & 1.01764 & Gas & 1.04425 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Evaluation table of term importance within the lexicon. The causes of emergencies in gas pipeline networks are diverse and complex, with considerable interactions among various factors. Analyzing causes is crucial for assessing network vulnerability, conducting dynamic risk assessments, managing risks, evaluating accident consequences, studying disaster mechanisms, and analyzing accident impacts. To assess the effectiveness of the domain-specific lexicon, we introduced a task to visualize the reduced dimensionality of word embeddings for causes of emergencies in gas pipeline networks. These data and their identifiers are detailed in Table 9.  
Emergencies in gas pipeline networks are categorized by human-related factors, equipment-related factors, and other factors. Initially, word embeddings are generated for these causes, and then their dimensionality is reduced to two dimensions using t-SNE. The results are shown in Figure 8. Distinct spatial separations among points of different colors are evident, with equipment-related factors (red) typically in different regions from human-related factors (blue) and other factors (green). Clustering, represented by ellipses, shows that most points within each cluster share the same color, indicating a high degree of internal consistency and excellent clustering quality. The figure may also display some boundary or outlier points situated on the borders between different colored zones or distant from the primary clusters. These occurrences suggest complex structures in higher-dimensional spaces or unique characteristics of some data points that are hard to detect.