The paper explores the application of ranking-based opinion mining in the travel domain in Myanmar. The study uses natural language processing techniques to extract and analyze opinions from online reviews of hotels in Myanmar. The study addresses the challenges posed by the Myanmar language, which is complex and has limited resources for language processing.
The study uses a ranking-based approach to opinion mining, where opinions are ranked based on their relevance and importance. The study identifies the top features that influence travelers’ opinions in the Myanmar travel domain, which include cleanliness, location, staff performance, and facilities. The study also identifies the sentiment towards these features, which includes positive, negative, and neutral sentiments.
The study shows that the ranking-based approach is effective in identifying the most relevant and important opinions from online reviews. The study also shows that the approach is useful in identifying the key features that influence travelers’ opinions in the Myanmar travel domain. The study concludes that the ranking-based approach can be a useful tool for businesses and policymakers in the travel industry in Myanmar to understand customer preferences and improve their services.
Overall, the paper highlights the potential benefits of opinion mining in the travel domain in Myanmar and suggests that the ranking-based approach can be an effective method for extracting and analyzing opinions from online reviews. The study also highlights the need for more research on the application of natural language processing techniques in the Myanmar language to address the challenges posed by the language.