Abstract:
Web users write reviews, blogs, and comments about products, hotels, news, and topics. Web users read reviews to decide on purchases, movies, restaurants, etc. User opinions are in reviews. Web users struggle to read and comprehend many reviews. Review opinion mining and summarization can reveal useful information.
This project will have a hotel review web app. Sentence review. System will extract keywords from sentence, mine database, and rate hotels based on user reviews. We presented sentence relevance score-based opinion summarization and machine learning and Sentiment Word Net-based opinion mining from hotel reviews.
Web users can quickly understand hotel review content with classified and summarized information. Opinion Mining for Hotel Review detects hidden sentiments in customer feedback and rates it accordingly. Opinion mining achieves system functionality. A web app called opinion mining for hotel reviews analyzes user feedback.
Based on user reviews, the system rates hotels as good, bad, or worst. We rank user reviews using a database of sentiment-based keywords with positivity or negativity weights. User reviews hotels after logging in. System will rank review by matching keywords in database.
Review rank determines hotel rating. Admins add new hotels and keywords to the database. This app helps travelers. This app helps frequent travelers. This app lets users find their ideal hotel. User can choose hotel before arriving.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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