## 3 Methodology
### Preprocessing Module
These evaluations involved comparisons with contemporary unsupervised, supervised, and hybrid methods on identical datasets. The experimental findings underscore the effectiveness of the proposed approach in aspect-term extraction across various datasets, while this proposed approach may not consistently yield the highest F-measure in every dataset, it consistently demonstrates competitive performance and, in certain instances, even outperforms alternative methodologies. This indicates the versatility and reliability of our model in capturing aspect terms across diverse contexts. Experimental evidence confirms the hypotheses that LOD's semantic capabilities help enhance the performance of ATE. This research has potential applications and benefits for a variety of industries, including tourism companies, restaurants, and e-commerce. For instance, comprehending the reviewer's opinion on the meal or constructing recommended systems that propose restaurants according to user preferences, such as suggesting a restaurant with a vibrant ambiance. In future endeavors, this research may explore the development of an automatic ontology creation process to supplant the corpus for aspect extraction. This would aim to enhance the semantic relationships between aspects and facilitate more accurate aspect terms extraction and aspect type classifications. Conceptualization, W.S. ; methodology, W.S. ; validation, W.S., N.A.-I. and W.W.; investigation, W.S. and N.A.-I. ; resources, W.S. ; writing--original draft preparation, W.S. and N.A.-I. ; writing--review and editing, W.S., N.A.-I. and W.W.; visualization, W.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The authors declare no conflicts of interest. ## References

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