Collaborative Filtering based Hotel Recommendation System using NLP

Modern hotels increasingly use customized suggestions to enhance customer satisfaction and advance encounter quality in the present digital era. Collaborative Filtering stands as a widely used method to predict user patterns via thing or customer similarity analysis and we extend its application through integration of NLP for processing text comments about bookings. The system provides detailed data-informed advice by assessing both numerical assessment data and subjective survey results to formulate complete recommendation solutions. Relevancy suggests that uniting collaborative filtering techniques with NLP analysis provides the hospitality industry with transformative suggestions strategies.