# Named Entity Recognition Method Based on Multi-Feature Fusion
## 4 Experimental Results
### Named Entity Recognition
#### 4.3.5 Experimental Results Analysis  
The number of entities of each attribute word extracted is shown in Table 5, where the number of attributes reflects the attention and evaluation of tourists in different attributes of the scenic spot. First of all, from the perspective of \"queuing time\", this attribute has the largest number of entities, indicating that queuing time is one of the most important factors in the tourist experience. Tourists are very sensitive to this and have mentioned it many times in the comment text. It can be seen that long queuing times may directly affect the overall experience. \"Experience\" is the second largest entity attribute, indicating that tourists' feelings about the entire scenic spot are multi-dimensional, including services, scenic spot atmosphere and other aspects. These factors jointly affect tourists' overall evaluation of the scenic spot. In contrast, \"price\" and \"playability\" are also aspects that tourists care about, indicating that the reasonableness of price and the richness of scenic spot projects play an important role in the attraction of tourists. In particular, the small number of \"playability\" entities may mean that this attribute is more personalized, and different tourists have different evaluations on it, or the overall playability of the scenic spot is slightly lower in priority in the minds of tourists than actual factors such as queuing and price. \"Taste\" and \"transportation\" attributes also have a notable number of entities, reflecting that the quality of dining options within the park and the ease of transportation are important elements of visitor evaluation.  
These aspects, particularly for attractions that include dining services or require long-distance travel, significantly impact visitor satisfaction with their overall experience. Finally, the entity numbers for \"service\" highlight that service quality remains one of the key factors affecting visitor satisfaction. A positive service experience can significantly enhance visitors' overall rating of the scenic spots. In summary, these data reveal that visitors  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Comparison Models** & **P** & **R** & **F1** \\ \hline BERT–BiLSTM–CRF & 81.5180 & 60.9552 & 69.7527 \\ BERT–BiLSTM–DGCNN–MHA–CRF & 86.4540 & 83.8133 & 85.1132 \\ BERT–DGCNN–BiLSTM–MHA–CRF & 82.5836 & 77.7251 & 80.0807 \\ ELECTRA– & & 87.3572 & 86.0736 & 86.7107 \\ RoBERTa-wmm– & 86.1453 & 84.2144 & 85.1689 \\ Our model & 87.5413 & 86.1466 & 86.8383 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison results (%).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Entity** & **Train** & **Test** & **Dev** & **Total** \\ \hline queuing time & 1772 & 612 & 537 & 2921 \\ experience & 943 & 297 & 292 & 1532 \\ playability & 297 & 95 & 117 & 509 \\ price & 627 & 217 & 221 & 1095 \\ taste & 242 & 92 & 98 & 432 \\ transportation & 301 & 99 & 91 & 491 \\ service & 961 & 296 & 303 & 1560 \\ opinion words & 4735 & 1618 & 1553 & 7906 \\ total & 9878 & 3326 & 3211 & 16,415 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Results.  
focus on multiple aspects of the scenic spots, particularly queuing time, overall experience, service and price -- practical factors that directly affect their experience.